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1
Ng, Justin. "Artificial Neural Network-Based Robotic Control." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1846.
Full textAbstract:
Artificial neural networks (ANNs) are highly-capable alternatives to traditional problem solving schemes due to their ability to solve non-linear systems with a nonalgorithmic approach. The applications of ANNs range from process control to pattern recognition and, with increasing importance, robotics. This paper demonstrates continuous control of a robot using the deep deterministic policy gradients (DDPG) algorithm, an actor-critic reinforcement learning strategy, originally conceived by Google DeepMind. After training, the robot performs controlled locomotion within an enclosed area. The paper also details the robot design process and explores the challenges of implementation in a real-time system.
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Ionescu, Armand-Mihai. "Membrane computing: traces, neural inspired models, controls." Doctoral thesis, Universitat Rovira i Virgili, 2008. http://hdl.handle.net/10803/8790.
Full textAbstract:
Membrane Computing:Traces, Neural Inspired Models, Controls
Autor:
Armand-Mihai Ionescu
Directores:
Dr. Victor Mitrana
(URV)
Dr. Takashi Yokomori
(Universidad Waseda, Japón)
Resumen Castellano:
El presente trabajo está dedicado a una área muy activa del cálculo natural (que intenta descubrir la odalidad en la cual la naturaleza calcula, especialmente al nivel biológico), es decir el cálculo con membranas, y más preciso, a los modelos de membranas inspirados de la funcionalidad biológica de la neurona.
La disertación contribuye al área de cálculo con membranas en tres direcciones principales. Primero, introducimos una nueva manera de definir el resultado de una computación siguiendo los rastros de un objeto especificado dentro de una estructura celular o de una estructura neuronal. A continuación, nos acercamos al ámbito de la biología del cerebro, con el objetivo de obtener varias maneras de controlar la computación por medio de procesos que inhiben/de-inhiben. Tercero, introducimos e investigamos en detallo - aunque en una fase preliminar porque muchos aspectos tienen que ser clarificados - una clase de sistemas inspirados de la manera en la cual las neuronas cooperan por medio de spikes, pulsos eléctricos de formas idénticas.
English summary:
The present work is dedicated to a very active branch of natural computing (which tries to discover the way nature computes, especially at a biological level), namely membrane computing, more precisely, to those models of membrane systems mainly inspired from the functioning of the neural cell.
The present dissertation contributes to membrane computing in three main directions. First, we introduce a new way of defining the result of a computation by means of following the traces of a specified object within a cell structure or a neural structure. Then, we get closer to the biology of the brain, considering various ways to control the computation by means of inhibiting/de-inhibiting processes. Third, we introduce and investigate in a great - though preliminary, as many issues remain to be clarified - detail a class of P systems inspired from the way neurons cooperate by means of spikes, electrical pulses of identical shapes.
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Pegoraro, Caterina. "Finding novel Neural Crest regulators : Pfkfb4, a key glycolysis partner, controls Neural Crest early patterning in Xenopus laevis." Thesis, Paris 11, 2012. http://www.theses.fr/2012PA112374.
Full textAbstract:
La crête neurale (CN) est une population transitoire de cellules multipotentes qui émerge à la frontière entre l’ectoderme neural et non-neural, dans une région appelée la bordure neurale (BN). Lorsque la BN se soulève pour former le tube neural, les cellules de la CN subissent une transition épithélium-mésenchyme (TEM), et migrent de façon intensive dans l’ensemble de l’embryon pour atteindre leur destination finale et se différencier. Elles sont à l’origine de nombreux types de dérivés : neurones, cellules gliales, cartilage de la tête, os et tissus connectifs, cellules pigmentaires, cellules sympatho-adrenales. Tous ces processus sont régulés par l’action coordonnée de nombreux gènes qui forment un réseau de régulations génétiques complexe, au sein duquel de nombreuses interactions ont été décrites, même si de nombreuses relations restent à élucider à ce jour. Une mauvaise régulation de gènes normalement impliqués dans la formation de la CN provoque des malformations congénitales appelées neurocristopathies. Par ailleurs, la TEM subie par les cellules de CN avant leur migration est également observée dans les cellules cancéreuses acquérant des propriétés métastatiques. Les événements moléculaires et de nombreux gènes impliqués dans la TEM sont communs au développement de la CN et au cancer.Les liens existant entre le développement de la CN et les neurocristopathies, ainsi que les métastases, soulignent l’importance de l’étude du réseau de régulations génétiques permettant la formation de la CN et l’EMT.Au laboratoire, nous nous intéressons aux événements précoces d’induction et de spécification de la CN. Dans le but d’identifier les gènes préférentiellement impliqués dans le développement précoce de la CN et non dans la formation de l’ectoderme neural et non-neural, un crible a été effectué sur le transcriptome de différents tissus embryonnaires micro-disséqués. La validation des résultats de ce crible a permis d’identifier plusieurs gènes intéressants possédant une fonction potentielle dans la formation de la CN. Nous nous sommes particulièrement intéressés à deux d’entre eux, en raison de leur fonction originale comparée à la majorité des gènes impliqués dans le développement de la CN : serca1 et pfkfb4, un régulateur de l’homéostasie calcique et un régulateur de la glycolyse respectivement.Nous avons analysé les patrons d’expression des gènes des familles serca et pfkfb au cours du développement de Xenopus laevis. En raison de son expression spécifique dans la CN, nous avons étudié plus en détails le rôle de pfkfb4 dans la formation de la CN. Cette analyse a montré que pfkfb4 est nécessaire pour la spécification neurale et de la crête neurale.Toutefois, malgré son rôle documenté dans la glycolyse, le phénotype des morphants pfkfb4 dans l’embryon de Xenopus laevis n’est pas dû à une altération de la glycolyse.En conclusion, nos résultats démontrent l’existence d’un nouveau rôle non glycolytique pour Pfkfb4 au cours du développement embryonnaire de Xenopus LaevisNeural Crest (NC) is a transient population of multipotent cells that arises at the border between neural and non-neural ectoderm, in a region named the neural border (NB). As the neural border elevates to form the neural tube, NC cells undergo an Epithelial-To-Mesenchymal Transition (EMT), migrate extensively into the whole body to reach their final destinations and differentiate. They give rise to multiple derivatives: neurons and glia, head cartilage, bones and connective tissue, pigment cells, sympatho-adrenal cells. All these processes are regulated by the concerted actions of several genes that form a complex Gene Regulatory Network (GRN), in which many interactions have been elucidated, but even more relationships still need to be understood. Misregulation of genes normally involved in NC formation causes birth defects called neurocristopathies. Moreover, the EMT that NC cells undergo before migration also takes place when cancer cells become metastatic: the molecular events and many of the genes involved in EMT and migration are shared between NC development and cancer. The links with metastasis, neurocristopathies and the fact that still little is known about the earliest steps of NC formation, highlight the importance and the interest in understanding the Gene Regulatory Network (GRN) leading to NC formation and EMT.In the laboratory, we are interested in the early steps of NC induction and specification. In order to identify genes preferentially involved in early NC development compared to genes involved in neural and non-neural ectoderm formation, a transcriptome screen on different microdissected embryonic tissues has been performed. The validation of the results of the screen revealed several interesting genes with a potential function in NC formation. We focused particularly on two of them, due to their original function compared to the majority of the genes involved in NC development: serca1 and pfkfb4, a calcium homeostasis regulator and a glycolysis regulator respectively. We analysed the expression patterns of serca and pfkfb family genes during Xenopus laevis development. Then, due to its specific expression in NC, we studied more in details the role of pfkfb4 in NC formation. This analysis revealed that pfkfb4 is necessary for neural and neural crest specification. However, despite its known role in glycolysis, pfkfb4 morphant phenotype in Xenopus laevis embryos is not due to an alteration of the glycolytic pathway.In conclusion, our results reveal a novel extra-glycolytic role for Pfkfb4 during Xenopus laevis embryonic development
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Layshot, Nicholas Joseph. "MODELING OF A GYRO-STABILIZED HELICOPTER CAMERA SYSTEM USING NEURAL NETWORKS." DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/421.
Full textAbstract:
On-board gimbal systems for camera stabilization in helicopters are typically based on linear models. Such models, however, are inaccurate due to system nonlinearities and complexities. As an alternative approach, artificial neural networks can provide a more accurate model of the gimbal system based on their non-linear mapping and generalization capabilities.
This thesis investigates the applications of artificial neural networks to model the inertial characteristics (on the azimuth axis) of the inner gimbal in a gyro-stabilized multi-gimbal system. The neural network is trained with time-domain data obtained from gyro rate sensors of an actual camera system. The network performance is evaluated and compared with measured data and a traditional linear model. Computer simulation results show the neural network model fits well with the measured data and significantly outperforms a traditional model.
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Newman, Jonathan P. "Optogenetic feedback control of neural activity." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52973.
Full textAbstract:
Optogenetics is a set of technologies that enable optically triggered gain or loss of function in genetically specified populations of cells. Optogenetic methods have revolutionized experimental neuroscience by allowing precise excitation or inhibition of firing in specified neuronal populations embedded within complex, heterogeneous tissue. Although optogenetic tools have greatly improved our ability manipulate neural activity, they do not offer control of neural firing in the face of ongoing changes in network activity, plasticity, or sensory input. In this thesis, I develop a feedback control technology that automatically adjusts optical stimulation in real-time to precisely control network activity levels. I describe hardware and software tools, modes of optogenetic stimulation, and control algorithms required to achieve robust neural control over timescales ranging from seconds to days. I then demonstrate the scientific utility of these technologies in several experimental contexts. First, I investigate the role of connectivity in shaping the network encoding process using continuously-varying optical stimulation. I show that synaptic connectivity linearizes the neuronal response, verifying previous theoretical predictions. Next, I use long-term optogenetic feedback control to show that reductions in excitatory neurotransmission directly trigger homeostatic increases in synaptic strength. This result opposes a large body of literature on the subject and has significant implications for memory formation and maintenance. The technology presented in this thesis greatly enhances the precision with which optical stimulation can control neural activity, and allows causally related variables within neural circuits to be studied independently.
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Kelly, Bronwen Noreen. "The Coordination of Breathing and Swallowing Across the Human Lifespan: Implications for Neural Control." Thesis, University of Canterbury. Communication Disorders, 2006. http://hdl.handle.net/10092/1295.
Full textAbstract:
Our understanding of the neural control of breathing-swallowing coordination (BSC) is largely unclear. Although brainstem control is undoubtedly predominant, this research investigated the hypothesis that the cortex becomes increasingly influential in BSC between birth and adulthood. The main paradigm used to test this primary hypothesis was a comparison of BSC in conditions along a continuum of volitional through non-volitional swallowing on the basis of a decreasing level of cortical activation along this continuum. Voluntarily-initiated swallows during wakefulness were at one end of the continuum and reflexively-initiated swallows during sleep were at the other extreme. Non-volitional wakeful swallows were considered between these two conditions. The BSC of ten infants between birth and 1 year of age and twenty adults between the ages of 20 and 75 years was recorded using non-invasive time-locked recording methods. In order to apply the 'continuum-of-volition' paradigm to swallowing conditions in infants, BSC was monitored during nutritive (breast- or bottle-feeding), non-nutritive wake, and sleep swallows. Infants were monitored longitudinally to determine whether maturation of the cortex and corticobulbar tracts during the first year of life influenced the patterns of BSC. In adults, BSC was monitored during three non-nutritive conditions: volitional, spontaneous wake, and sleep conditions. Post-swallow expiration was found to be predominant in all conditions for all participants at all ages. In addition, the infant results revealed that nutritive BSC matured during the first year of life and differed to non-nutritive wakeful BSC, particularly in the first 2 months of life. Non-nutritive wakeful and sleep BSC did not differ from one another. In summary, the infant results support increasing cortical input into volitional nutritive BSC, an early impact of feeding on BSC, and no difference between BSC when asleep and non-volitional non-nutritive swallows when awake. The results obtained from adults revealed that irrespective of the level of arousal, volitional BSC is different to non-volitional BSC. These results imply that cortical influence on BSC is limited to conditions in which swallowing is voluntarily initiated. The combined interpretation of infant and adult results suggest that cortical influence over BSC, although increasing with maturation, is limited to the volitional swallowing conditions of feeding in infants and during non-nutritive but volitional swallows in adults. From this, it can be deduced that the most likely cortical sites involved in BSC are those involved in the voluntary initiation or planning of swallowing. Infant and adult swallowing apnoea duration (SAD) was also compared across all of the above conditions. SAD was influenced by feeding throughout the first year of life but was not influenced by level of arousal at any stage in the first year or in adulthood. Also, SAD did not change with age in any swallowing condition during infancy. However, comparison of non-nutritive wake SAD across the lifespan revealed that SAD of newborns and young adults is shorter than that of elderly adults, with no difference between consecutive age-groups: newborns, one-year-olds, and young adults. These results suggest SAD is largely mature at birth and impervious to descending suprabulbar influence. Finally, the effects of volitional swallowing and level of arousal on peak submental surface electromyography (SEMG) was investigated in adults. Like BSC, submental muscle activity was influenced only by volitional swallowing, being longer for volitional than non-volitional swallows without being influenced by level of arousal. Since peak submental SEMG activity represents a measure of relative hyolaryngeal excursion, these results suggest that the cortex has some degree of influence over this particular feature of pharyngeal-stage swallowing.
7
Kimball, Nicholas. "Utilizing Trajectory Optimization In The Training Of Neural Network Controllers." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2071.
Full textAbstract:
Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum system, it learns an effective policy up to three times faster than the other algorithms. In the cartpole system, it learns an effective policy up to nearly fifteen times faster than the other algorithms.
8
Smith, Bradley R. "Neural Network Enhancement of Closed-Loop Controllers for Ill-Modeled Systems with Unknown Nonlinearities." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/29607.
Full textAbstract:
The nonlinearities of a nonlinear system can degrade the performance of a closed-loop system. In order to improve the performance of the closed-loop system, an adaptive technique, using a neural network, was developed. A neural network is placed in series between the output of the fixed-gain controller and the input into the plant. The weights are initialized to values that result in a unity gain across the neural network, which is referred to as a "feed-through neural network." The initial unity gain causes the output of the neural network to be equal to the input of neural network at the beginning of the convergence process. The result is that the closed-loop system's performance with the neural network is, initially, equal to the closed-loop system's performance without the neural network.
As the weights of the neural network converge, the performance of the system improves. However, the back propagation algorithm was developed to update the weights of the feed-forward neural network in the open loop. Although the back propagation algorithm converged the weights in the closed loop, it worked very slowly. Two new update algorithms were developed for converging the weights of the neural network inside the closed-loop. The first algorithm was developed to make the convergence process independent of the plants dynamics and to correct for the effects of the closed loop. The second algorithm does not eliminate the effects of the plant's dynamics, but still does correct for the effects of the closed loop. Both algorithms are effective in converging the weights much faster than the back propagation algorithm. All of the update algorithms have been shown to work effectively on stable and unstable nonlinear plants.Ph. D.
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Barrett, Andrea Lynn. "A FGF-Hh feedback loop controls stem cell proliferation in the developing larval brain of drosophila melanogaster." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2017.
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Hudson, Christopher Allen. "Single-Phase, Single-Switch, Sensorless Switched Reluctance Motor Drive Utilizing a Minimal Artificial Neural Net." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/34735.
Full textAbstract:
Artificial Neural Networks (ANNs) have proved to be useful in approximating non-
linear systems in many applications including motion control. ANNs advocated in
switched reluctance motor (SRM) control typically have a large number of neurons
and several layers which impedes their real time implementation in embedded sys-
tems. Real time estimation at high speeds using these ANNs is diffcult due to the
high number of operations required to process the ANN controller. An insuffcient
availability of time between two sampling intervals limits the available computation
time for both processing the neural net and the other functions required for the motor
drive. One ideal application of ANNs in SRM control is rotor position estimation. Due
to reliability issues, elimination of the rotor position sensors is absolutely required for
high volume, high speed and low cost applications of SRM's. ANNs provide a means
by which drive designers can implement position sensorless drive technology that is
both robust and easily implemented.
It is demonstrated that a new and novel ANN configuration can be implemented
for accurate rotor position estimation in a sensorless SRM drive. Consisting of just
4 neurons, the neural estimator is the smallest of its kind for SRM rotor position
estimation. The breakthrough that provided the reduction was the addition of a non-
linear input. Typical input spaces for SRM position neural estimators consist of both
current,and fux-linkage. The neural network was trained on-line using these
inputs and a third, non-linear input provided by a preprocessed product of the two
typical inputs.Master of Science
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Imbeault, Sophie, Lianne Gauvin, Hadi Toeg, Alexandra Pettit, Catherine Sorbara, Lamiaa Migahed, Rebecca DesRoches, et al. "The extracellular matrix controls gap junction protein expression and function in postnatal hippocampal neural progenitor cells." BioMed Central, 2009. http://hdl.handle.net/10150/610072.
Full textAbstract:
BACKGROUND:Gap junction protein and extracellular matrix signalling systems act in concert to influence developmental specification of neural stem and progenitor cells. It is not known how these two signalling systems interact. Here, we examined the role of ECM components in regulating connexin expression and function in postnatal hippocampal progenitor cells.RESULTS:We found that Cx26, Cx29, Cx30, Cx37, Cx40, Cx43, Cx45, and Cx47 mRNA and protein but only Cx32 and Cx36 mRNA are detected in distinct neural progenitor cell populations cultured in the absence of exogenous ECM. Multipotential Type 1 cells express Cx26, Cx30, and Cx43 protein. Their Type 2a progeny but not Type 2b and 3 neuronally committed progenitor cells additionally express Cx37, Cx40, and Cx45. Cx29 and Cx47 protein is detected in early oligodendrocyte progenitors and mature oligodendrocytes respectively. Engagement with a laminin substrate markedly increases Cx26 protein expression, decreases Cx40, Cx43, Cx45, and Cx47 protein expression, and alters subcellular localization of Cx30. These changes are associated with decreased neurogenesis. Further, laminin elicits the appearance of Cx32 protein in early oligodendrocyte progenitors and Cx36 protein in immature neurons. These changes impact upon functional connexin-mediated hemichannel activity but not gap junctional intercellular communication.CONCLUSION:Together, these findings demonstrate a new role for extracellular matrix-cell interaction, specifically laminin, in the regulation of intrinsic connexin expression and function in postnatal neural progenitor cells.
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Voyatzis, Sylvie. "Neural activity controls retinotopic projections in the superior collicul us by modulating axon retraction and cell survival." Paris 6, 2009. http://www.theses.fr/2009PA066311.
Full textAbstract:
L’activité spontanée joue un rôle important dans le développement des cartes retinotopiques. Nous avons utilisé un model de co-culture qui récapitule la mise en place de la carte retino-colliculaire afin de déterminer où l’activité agit. Nous avons démontré que l’activité neuronale est requise pour la rétraction des axones rétiniens induite par les éphrine-As. Elle nécessite l’entrée de calcium par des canaux calciques de type-L et des stocks internes de calcium. Nous avons déterminé que des fluctuations d’AMPc et de la PKA sont aussi essentielles. Nous avons cherché à montrer l’existence d’oscillations d’AMPc grâce à une technique d’imagerie basée sur le principe du FRET. Nous avons analysé la maturation des types cellulaires rétiniens au cours de la co-culture, afin de déterminer les circuits neuronaux sous-tendant l’émergence de l’activité spontanée. Nous avons analysé la mort cellulaire d’une population de CGR. Nous avons montré que la diminution du nombre de CGR avait lieu entre DIV4 et DIV7, correspondant à la période P0 à P3 : le pic de mort cellulaire développementale in vivo. Cette mort cellulaire dépend de la cible et de l’activité neuronale.
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Álvarez, Medina José Roberto. "Integration of SHH and WNT pathways controls morphogenesis of the CNS." Doctoral thesis, Universitat de Barcelona, 2008. http://hdl.handle.net/10803/1894.
Full textAbstract:
Dorsoventral patterning of the vertebrate nervous system is achieved by the combined activity of morphogenetic signals secreted from dorsal and ventral signalling centres. The Shh/Gli pathway plays a major role in patterning the ventral neural tube; however, the molecular mechanisms that limit target gene responses to specific progenitor domains remain unclear. Here, we show that Wnt1 and Wnt3a, by signalling through the canonical β-catenin/Tcf pathway, control expression of dorsal genes and suppression of the ventral programme, and thatthis role in DV patterning depends on Gli activity. Additionally, we show that Gli3 expression is controlled by Wnt activity. Identification and characterization of highly conserved non-coding DNA regions around the human Gli3 gene revealed the presence of transcriptionally active Tcf-binding sequences. These indicated that dorsal Gli3 expression might be directly regulated by canonical Wnt activity. In turn, Gli3, by acting as a transcriptional repressor, restricted graded Shh/Gli ventral activity to properly pattern the spinal cord.
Additionally, the Wnt canonical pathway and Hedgehog signalling have been linked to cell proliferation in a variety of systems, however interaction of these pathways to control cell cycle progression have not been studied. In the developing vertebrate nervous system, although Shh and Wnt ligands are expressed at the opposite ventral and dorsal signalling centres, reports demonstrate that proliferation of neural progenitors require both activities throughout the dorsoventral axis. Here we demonstrate the integration of both pathways to control the length of G1 phase, and the absolute requirement of an upstream Hedgehog activity for the Wnt-mediated regulation of the key cell cycle activator CyclinD1 expression and for G1 progression. Although Wnt canonical activity appeared restricted to the control of G1 phase, Hedgehog activity additionally regulates the length of G2 phase through the regulation of ate cell cycle activators such as CyclinA2 and CyclinB2/3. These findings support a key role for Hedgehog in growth control, as a regulator of G1 and G2 phases of cell cycle and importantly as an upstream regulator of the canonical Wnt activity.
KEY WORDS: SHH, WNT, Neural Tube, Patterning, CNS, Cell Cycle.
"La integración de las vías de señalización de Shh y Wnt controla la morfogénesis del SNC"
TEXTO:
La formación del patrón dorsoventral del sistema nervioso central en vertebrados está controlada por la acción de señales morfogenéticas. Estas
señales son secretadas por centros de señalización situados en el extremo dorsal, ectodermo y placa del techo, y ventral, notocorda y placa del suelo, del tubo neural. La vía de señalización de Shh/Gli juega un papel principal en el establecimiento temprano de la región ventral del tubo neural. Sin embargo, los
mecanismos moleculares que restringen la expresión de los genes responsables de establecer este patrón a un dominio concreto no son del todo conocidos. En este trabajo mostramos que las señales morphogenéticas Wnt1
y Wnt3a, activando la vía de señalización canónica mediada por β-catenina/Tcf, regulan la expresión de genes dorsales y reprimen el programa ventral, mediante un mecanismo que depende de la actividad Gli. Además, mostramos
que la expresión de Gli3 está controlada por la vía de Wnt. La identificación y caracterización de regiones no codificantes altamente conservadas alrededor del locus de Gli3 humano revela que contienen sitios de unión consenso para los factores Tcf/Lef-1 activos. Esto indica que la expresión dorsal de Gli3 está controlada directamente por la actividad de la vía canónica de Wnt. A su vez, Gli3, actuando como un represor transcripcional, restringe la actividad del gradiente ventral Shh/Gli para establecer el patrón dorsoventral del tubo neural correctamente.
Por otro lado, las vías canónicas de señalización celular de Wnt y Hedgehog regulan la proliferación celular en varios contextos de forma conjunta, Sin embargo, posiblesm interacciones de estas vías de señalización en el control del ciclo celular no han siso estudiadas. Durante el desarrollo del sistema nervioso de vertebrados, aunque las proteínas Shh y Wnts se expresan en extremos dorso-ventralmente opuestos del tubo neural, varios trabajos demuestran que la proliferación de los progenitores neuronales requiere ambas actividades a lo largo de todo el eje dorsoventral. En este trabajo, demostramos que es
necesaria la integración de ambas vías de señalización para controlar la duración de la fase G1 del ciclo celular. Además, mostramos el requerimiento de la actividad Hedgehog para la regulación mediada por Wnt de la expresión del activador de ciclo celular ciclina D1, componente clave para la progresión a
través de G1. Aunque la actividad de la vía canónica de Wnt se limita al control de la transición G1/S, adicionalmente, la actividad Hedgehog regula la duración de la fase G2 mediante la regulación de las ciclinas de fase G2 ciclina A2 y Ciclinas B2/B3. En conjunto, estos resultados proponen un papel fundamental
en el control del crecimiento para la actividad Shh/Gli como reguladora de las fases G1 y G2 del ciclo celular y además como reguladora por encima de la actividad canónica de Wnt.
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Li-Kroeger, David. "Integration of regional and neural transcription factors controls EGF signaling from sensory organ precursor cells during Drosophila development." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337351052.
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Limbachia, Chirag Bharatkumar. "Neural Correlates of Convergence Eye Movements in Convergence Insufficiency Patients vs. Normal Binocular Vision Controls: An fMRI Study." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1453206183.
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Neuhouser, Marian L. Stone. "Absorption of pteroylglutamic acid and pteroylpolyglutamic acid in women with a history of neural tube defect affected pregnancies vs. controls /." Thesis, Connect to this title online; UW restricted, 1996. http://hdl.handle.net/1773/6613.
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Wilmot, Timothy Allen Jr. "Intelligent Controls for a Semi-Active Hydraulic Prosthetic Knee." Cleveland State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=csu1315531357.
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Pfeifer, Gaby. "The neural processes underpinning visual associative memory : a comparison of young grapheme-colour synaesthetes, older adults and young controls." Thesis, University of Brighton, 2015. https://research.brighton.ac.uk/en/studentTheses/e1f2f7c9-099e-4817-ac75-a5a0e7e6c018.
Full textAbstract:
The traditional modular account of memory segregates visual associative memory and visual perception, with the former underpinned by the medial temporal lobes (MTL) and the latter by posterior visual regions. By contrast, the representational account of memory envisages visual associative memory as a perceptual-mnemonic continuum that can be traced from early visual cortex to anterior MTL structures. In this thesis, we tested these fundamentally different memory models by using a novel between-group design with young grapheme-colour synaesthetes, older adults and young controls, each of whom have their respective strengths and weaknesses in memory and perception. Specifically, grapheme-colour synaesthetes possess enhanced perceptual mechanisms, allowing them to experience black letters, words or digits as inherently coloured. They also show enhanced early visual cortex sensitivity in response to non-synaesthesia inducing stimuli (Barnett et al., 2008) as well as enhanced memory for verbal and visual stimuli. Using psychophysical techniques and functional magnetic resonance imaging (fMRI), we compared these three groups on a range of cognitive processes involved in visual associative memory: encoding, working memory, associative retrieval and recognition.
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Ghasemalizadeh, Omid. "Analysis and Development of Control Methodologies for Semi-active Suspensions." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73445.
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Semi-active suspensions have drawn particular attention due to their superior performance over the other types of suspensions. One of their advantages is that their damping coefficient can be controlled without the need for any external source of power. In this study, a handful of control approaches are implemented on a car models using MATLAB/Simulink. The investigated control methodologies are skyhook, groundhook, hybrid skyhook-groundhook, Acceleration Driven Damper, Power Driven Damper, H∞ Robust Control, Fuzzy Logic Controller, and Inverse ANFIS. H∞ Robust Control is an advanced method that guarantees transient performance and rejects external disturbances. It is shown that H∞ with the proposed modification, has the best performance although its relatively high cost of computation could be potentially considered as a drawback. Also, the proposed Inverse ANFIS controller uses the power of fuzzy systems along with neural networks to help improve vehicle ride metrics significantly.
In this study, a novel approach is introduced to analyze and fine-tune semi-active suspension control algorithms. In some cases, such as military trucks moving on off-road terrains, it is critical to keep the vehicle ride quality in an acceptable range. Semi-active suspensions are used to have more control over the ride metrics compared to passive suspensions and also, be more cost-effective compared to active suspensions. The proposed methodology will investigate the skyhook-groundhook hybrid controller. This is accomplished by conducting sensitivity analysis of the controller performance to varying vehicle/road parameters. This approach utilizes sensitivity analysis and one-at-a-time methodology to find and reach the optimum point of vehicle suspensions. Furthermore, real-time tuning of the mentioned controller will be studied. The online tuning will help keep the ride quality of the vehicle close to its optimum point while the vehicle parameters are changing. A quarter-car model is used for all simulations and analyses.Ph. D.
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Thomas, Kim. "Incident detection on arterials using neural network data fusion of simulated probe vehicle and loop detector data /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18433.pdf.
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Biruk, David D. "Neural Network Based Control of Integrated Recycle Heat Exchanger Superheaters in Circulating Fluidized Bed Boilers." UNF Digital Commons, 2013. http://digitalcommons.unf.edu/etd/470.
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The focus of this thesis is the development and implementation of a neural network model predictive controller to be used for controlling the integrated recycle heat exchanger (Intrex) in a 300MW circulating fluidized bed (CFB) boiler. Discussion of the development of the controller will include data collection and preprocessing, controller design and controller tuning. The controller will be programmed directly into the plant distributed control system (DCS) and does not require the continuous use of any third party software.
The intrexes serve as the loop seal in the CFB as well as intermediate and finishing superheaters. Heat is transferred to the steam in the intrex superheaters from the circulating ash which can vary in consistency, quantity and quality. Fuel composition can have a large impact on the ash quality and in turn, on intrex performance. Variations in MW load and airflow settings will also impact intrex performance due to their impact on the quantity of ash circulating in the CFB. Insufficient intrex heat transfer will result in low main steam temperature while excessive heat transfer will result in high superheat attemperator sprays and/or loss of unit efficiency.
This controller will automatically adjust to optimize intrex ash flow to compensate for changes in the other ash properties by controlling intrex air flows. The controller will allow the operator to enter a target intrex steam temperature increase which will cause all of the intrex air flows to adjust simultaneously to achieve the target temperature. The result will be stable main steam temperature and in turn stable and reliable operation of the CFB.
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Peruzzi, Pierpaolo. "MiR-128 controls the activity of Polycomb Repressor Complexes 1 and 2 in Neural Stem Cells: Implications of its loss in gliomagenesis." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366055621.
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Makedonopoulou, Paraskevi. "Studying the molecular consequences of the t(1;11) balanced translocation using iPSCs derived from carriers and within family controls." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/25871.
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Schizophrenia is a major psychiatric disorder that affects 1% of the world population and is among the 10 leading worldwide causes of disability. Disrupted-In- Schizophrenia (DISC1) is one of the most studied risk genes for mental illness and is disrupted by a balanced translocation between chromosomes 1 and 11 that co-segregates with major mental illness in a single large Scottish family. DISC1 is a scaffold protein with numerous interactors and has been shown to hold key roles in neuronal progenitor proliferation, migration, cells signalling and synapse formation and maintenance. The studies herein provide the platform in order to investigate the molecular and cellular consequences of the t(1;11) translocation using induced pluripotent stem cells (iPSCs)-derived neural precursor cells and neurons from within-family carriers and controls. Towards this end, several iPSC lines have been converted into neural progenitor cells (NPCs) and differentiated into physiologically active forebrain neurons following well-characterised protocols. These cells were characterised in terms of basic marker expression at each developmental stage. Inter-line variation was observed in all subsequent experiments but overall t(1;11) lines did not generate less neuronal or less proliferating cells compared to control lines. Furthermore, the expression pattern of genes disrupted by the t(1;11) translocation was investigated by RT-qPCR. DISC1 was reduced by ~50% in the translocation lines, both neural precursors and neurons. This observation corresponds to previous findings in lymphoblastoid cell lines (LBCs) derived from members of the same family. Moreover, DISC1 expression was found to increase as neural precursors differentiation to neurons. Two other genes are disrupted by the t(1;11) translocation;DISC2 and DISC1FP1. Their expression was detectable, but below the threshold of quantification. Similarly, DISC1/DISC1FP1 chimeric transcripts corresponding to such transcripts previously identifies in LBCs from the family were detectable, but not quantifiable. A fourth gene, TSNAX, was also investigated because it is located in close proximity to, and undergoes intergenic splicing with, DISC1. Interestingly, TSNAX was found to be altered in some but not all time points studied, in the translocation carriers compared to control lines. In addition to breakpoint gene expression profiling, iPSC-derived material was used to investigate neuronal differentiation. There seemed to be attenuation in BIII-TUBULIN expression at two weeks post-differentiation, while NESTIN, MAP2 and GFAP expression was similar between translocation carrier and control lines at all time points studied. I also had access to targeted mice designed to mimic the derived chromosome 1 of the t(1;11) balanced translocation. Using RT-qPCR Disc1 expression was found to be 50% lower in heterozygous mice compared to wild types, and I detected a similar profile of chimeric transcript expression as detected in translocation carrier-derived LBCs. These observations support my gene expression studies of the human cells and indicate that the iPSC-derived neural precursors and neurons can be studied in parallel with the genome edited mice to obtain meaningful insights into the mechanism by which the t(1;11) translocation confers substantially elevated risk of major mental illness. In conclusion, the studies described in this thesis provide an experimental platform for investigation of the effects of the t(1;11) translocation upon function and gene and protein expression in material derived from translocation carriers and in brain tissue from a corresponding mouse model.
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Henco, Lara [Verfasser], and Leonhard [Akademischer Betreuer] Schilbach. "Using Bayesian modelling to uncover the behavioural and neural mechanisms of social learning and decision-making in healthy controls & psychiatric disorders / Lara Henco ; Betreuer: Leonhard Schilbach." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2020. http://d-nb.info/1234911442/34.
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Ariza, Zambrano William Camilo 1989. "Controle ativo de vibrações usando redes neurais artificiais : Active vibration control using artificial neural networks." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/264927.
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Orientador: Alberto Luiz SerpaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica
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Resumo: Este trabalho tem como objetivo principal o estudo de um método de controle baseado no uso de redes neurais artificiais aplicado ao problema de controle de vibrações em estruturas flexíveis. Este trabalho centra-se no estudo do esquema de controle inverso-direto, que consiste em identificar a dinâmica inversa da planta através de uma rede neural artificial para ser usada como controlador. Três exemplos de aplicação foram resolvidos utilizando-se controladores projetados com o método inverso-direto. A primeira aplicação é o controle de vibrações em uma estrutura mecânica de parâmetros concentrados. O segundo exemplo de aplicação é o controle de vibrações de uma placa engastada em uma de suas extremidades. Neste caso, a placa engastada foi modelada utilizando-se o método de elementos finitos. No seguinte exemplo, o modelo da placa usado no exemplo anterior foi reduzido, deixando apenas os primeiros modos de vibração. No último exemplo tratou-se o problema de controle não colocado das vibrações em uma placa engastada. Os resultados foram analisados a partir da resposta temporal e da resposta em frequência do sistema em malha fechada. Para comparar os resultados obtidos utilizando-se o método de controle baseado em redes neurais artificiais, os exemplos citados anteriormente foram também resolvidos utilizando-se o método de controle ??. Os resultados obtidos demonstram que o método de controle baseado em modelo inverso usando redes neurais foi eficaz na resolução deste tipo de problema
Abstract: The goal of this work is to study a control method based on artificial neural networks applied to the vibration control of flexible structures problem. This work focuses in the direct-inverse control scheme which consists of identifing the inverse dynamics of the plant through an artificial neural network to be used as the controller. Three application examples using the direct-inverse method were solved. The first application is the vibration control in a mechanical structure of concentrated parameters. The second application example is the vibration control of a cantilever plate. The cantilever plate was modeled using the finite elements method. In the third example, a reduction of the cantilever plate model was made. In the last example a non-collocated control problem of vibration in a cantilever plate was treated. The results of the scheme were evaluated according to the temporal response and the frequency response of the closed-loop system. In order to compare the results obtained using the control method based on artificial neural networks, the previous examples were also solved using the ?? control method. The obtained results show that the control method based on inverse model using neural networks was effective in solving this kind of problem
Mestrado
Mecanica dos Sólidos e Projeto Mecanico
Mestre em Engenharia Mecânica
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Eyng, Eduardo. "Controle feedforward-feedback aplicado as colunas de absorção do processo de produção de etanol por fermentação." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/267254.
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Orientador: Ana Maria Frattini FiletiTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica
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Resumo: O etanol perdido por evaporacao durante o processo de producao por fermentação pode ser recuperado por uma coluna de absorcao, a qual requer um sistema de controle robusto de acordo com sua complexidade. Este equipamento tambem e utilizado no tratamento do CO2, um co-produto deste processo. Neste sentido, no presente trabalho foi proposto e testado, o emprego de controladores feedforward-feedback, baseados em modelo inverso de redes neurais, os quais manipulam as vazoes de solvente que sao alimentados as colunas, para controlar a concentracao de etanol na corrente gasosa a saida da primeira coluna, e a concentracao de agua residual no efluente gasoso da segunda. Simulacoes foram feitas, sendo abordado tanto o problema regulatorio quanto o problema servo para as duas colunas de absorcao do processo estudado. O desempenho do controlador neural foi superior ao apresentado por um controlador convencional PID, para ambas as colunas de absorcao estudadas, pois o tempo de resposta, assim como o overshoot foi menor. A superioridade do controlador neural foi comprovada pelos valores obtidos para os parametros ITAE (integral do erro absoluto ponderada pelo tempo), IAE (integral do erro absoluto) e ISE (integral do quadrado do erro). Outro objetivo deste trabalho foi avaliar a influencia das incertezas nos sensores sobre o desempenho do sistema de controle. Foram testados tres niveis: 5, 10 e 15%, sendo as incertezas inseridas nas variaveis de entrada do tipo concentracao de etanol/agua residual na corrente gasosa. Para a coluna de recuperacao de etanol, tanto para o problema regulatorio quanto servo, nenhum controlador conseguiu estabilizar a variavel controlada no set point, no entanto, quando empregado o controlador neural a amplitude da faixa de oscilacao da variavel controlada foi menor para todos os niveis de incerteza testados. Já para a coluna de tratamento de CO2, os controladores encontraram dificuldades em manter a estabilidade do sistema. Neste sentido, o controlador neural apresentou um desempenho satisfatorio para incertezas de 5 e 10%, enquanto que o PID nao conseguiu manter o sistema estavel para incertezas superiores a 5%. Com base nos testes realizados foi constatado que o controlador neural proposto constitui uma opcao atrativa para o controle das colunas de absorcao do processo deproducao de etanol por fermentacao, principalmente quando os niveis de incerteza forem de ate 10%.
Abstract: Some of ethanol lost by evaporation during its fermentation production process may be recovered using an absorption column, which requires a robust control system. This equipment also is used on carbonic gas treatment, a by-product of this process. In the present work, the development of nonlinear feedforward-feedback controllers, based on a neural network inverse model, was proposed and tested to manipulate the absorbent flow rates in order to control the residual ethanol concentration in the effluent gas phase at the first absorption column, and the residual water at the second one. Simulation studies were carried out for the regulator and servo problem, for both absorption columns studied. The neural controller proposed outperformed a conventional PID, because the response time, and also the overshoot were smaller when the neural controller was applied. The results were confirmed by the ITAE (integral of time multiplied by the absolute error), IAE (integral of absolute error) and ISE (integral of square error) parameters. The measurement uncertainties influence on control system performance was tested for three levels: 5, 10 and 15%. The uncertainties were introduced on ethanol/residual water concentration on gas phase. For the ethanol recovery column, neither PID nor the neural controller drove the controlled variable exactly to the set point, however, the neural controller provided a smaller oscillation for all uncertainty levels tested, for regulator and servo problem. The neural controller also outperformed PID in CO2 treatment column. For the regulator and servo problems the neural controller successfully proceeded when the uncertainty level was 5% or 10%, while the PID did not deal adequately with uncertainties above 5%. Therefore, the proposed neural controller proved be an attractive control solution for the absorption columns of ethanol production process by fermentation, especially when the input variables carry small uncertainties ( less than 10%) from the sensors.
Doutorado
Sistemas de Processos Quimicos e Informatica
Doutor em Engenharia Química
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Sireci, Alexander. "DC-DC Converter Control System for the Energy Harvesting from Exercise Machines System." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1747.
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Current exercise machines create resistance to motion and dissipate energy as heat. Some companies create ways to harness this energy, but not cost-effectively. The Energy Harvesting from Exercise Machines (EHFEM) project reduces the cost of harnessing the renewable energy. The system architecture includes the elliptical exercise machines outputting power to DC-DC converters, which then connects to the microinverters. All microinverter outputs tie together and then connect to the grid. The control system, placed around the DC-DC converters, quickly detects changes in current, and limits the current to prevent the DC-DC converters and microinverters from entering failure states.
An artificial neural network learns to mitigate incohesive microinverter and DC-DC converter actions. The DC-DC converter outputs 36 V DC operating within its specifications, but the microinverter drops input resistance looking for the sharp decrease in power that a solar panel exhibits. Since the DC-DC converter behaves according to Ohm’s Law, the inverter sees no decrease in power until the voltage drops below the microinverter’s minimum input voltage. Once the microinverter turns off, the converter regulates as intended and turns the microinverter back on only to repeat this detrimental cycle. Training the neural network with the back propagation algorithm outputs a value corresponding to the feedback voltage, which increases or decreases the voltage applied from the resistive feedback in the DC-DC converter.
In order for the system to react well to changes on the order of tens of microseconds, it must read ADC values and compute the output neuron value quicker than previous control attempts. Measured voltages and currents entering and leaving the DC-DC converter constitute the neural network’s input neurons. Current and voltage sensing circuit designs include low-pass filtering to reduce software noise filtering in the interest of speed. The complete solution slightly reduces the efficiency of the system under a constant load due to additional component power dissipation, while actually increasing it under the expected varying loads.
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Popoff, Luiz Henrique Gomes. "Controle preditivo neural aplicado ? processos petroqu?micos." Universidade Federal do Rio Grande do Norte, 2009. http://repositorio.ufrn.br:8080/jspui/handle/123456789/12922.
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Previous issue date: 2009-08-07A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH ? um processo de grande import?ncia na ind?stria petroqu?mica, onde se deseja manter constante o n?vel de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho est?tico e din?mica n?olineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um respons?vel pela identifica??o e outro pelo o c?lculo do sinal de controle. Para realizar a identifica??o neural ? utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propaga??o Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e sa?da da planta ? iniciado o treinamento offline da rede. Dessa forma, os pesos sin?pticos s?o ajustados e a rede est? apta para representar o sistema com a m?xima precis?o poss?vel. O modelo neural gerado ? usado para predizer as sa?das futuras do sistema, com isso o otimizador calcula uma s?rie de a??es de controle, atrav?s da minimiza??o de uma fun??o objetivo quadr?tica, fazendo com que a sa?da do processo siga um sinal de refer?ncia desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identifica??o, via redes neurais e o segundo ? respons?vel pelo controle do processo. As ferramentas aqui implementadas e aplicadas s?o gen?ricas, ambas permitem a aplica??o da estrutura de controle a qualquer novo processo
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Dall´Agnol, Marcelo. "Aplicação de controladores feedback em sistema experimental de refrigeração e desenvolvimento de modelo preditivo baseado em redes neurais." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266964.
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Orientadores: Ana Maria Frattini Fileti, Flávio Vasconcelos da SilvaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química
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Resumo: O presente trabalho teve por objetivo propor uma sistemática para identificação de um sistema de refrigeração dotado de compressor e bomba de fluido secundário de rotação variável, para a aplicação futura de alternativas de controle multivariáveis com foco na redução do consumo de energia e otimização do coeficiente de performance (COP) de tais sistemas. Uma primeira etapa de ensaios experimentais foi realizada para gerar um conhecimento prévio do sistema, caracterizando-o como não-linear. Foram utilizadas diversas arquiteturas de redes neurais artificiais (RNA) para gerar modelos não-lineares MIMO (Multiple Input-Multiple Output), através do software MATLAB® para fazer a predição das temperaturas de evaporação e do fluido secundário. Para treinamento da rede neural foram utilizados dados de ensaios em malha aberta e malha fechada com um controlador PID desenvolvido especialmente para este fim. Neste sistema de controle PID foram utilizadas técnicas como anti-windup e derivative-kick na tentativa de melhorar a atuação de tal controlador. O PID, apesar de conseguir controlar o sistema em torno de 2°C, mostrou-se pouco eficiente quando eram aplicados degraus no set-point e na carga elétrica. A modelagem não-linear resultou em uma rede neural com arquitetura 11x2x8x2 que foi capaz de prever as duas temperaturas com precisão de mais ou menos 0,5°C, mesmo quando o sistema de refrigeração se manteve instável.
Abstract: The main aim of the present work was to propose a systematic identification procedure for an experimental refrigeration system operating under variable rotation speed compressor and pump of secondary fluid. This work will find future applications in alternative multivariable control development with focus on reducing energy consumption and on the optimization of the coefficient of performance (COP) of such systems. The nonlinear feature of the system was proved by means of imposed speed disturbances process reaction curves. Using the software MATLAB? Various artificial neural networks (ANN) architectures were used to generate non-linear models with Multiple-Input-Multiple-Output (MIMO) variables, in order to predict the evaporation and the secondary fluid temperatures. Open-loop and also closed loop assays were carried out and the experimental data used in the neural network training procedure. A specially designed PID, using anti-windup and derivative-kick techniques, was employed in the closed-loop runs. This conventional temperature controller showed an acceptable off-set of 2°C, however some instability occurred when set point and thermal load changed. The best non-linear modeling resulted in a neural network with architecture 11x2x8x2. This neural model was able to predict the two temperatures with precision of about 0.5°C, even when the refrigeration system remained unstable.
Mestrado
Sistemas de Processos Quimicos e Informatica
Mestre em Engenharia Química
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Enjin, Anders. "Neural Control of Movement : Motor Neuron Subtypes, Proprioception and Recurrent Inhibition." Doctoral thesis, Uppsala universitet, Genetisk utvecklingsbiologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-147361.
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Movement is central for life, and all animals depend on accurate regulation of movement for purposeful behavior. There is great diversity of movements, ranging between simple and vital breathing movements to minute and subtle movements of the face used to communicate emotions. Consequently, motor neurons, which are the only route of central nervous system output, are essential for all motor behaviors. To control the many motor behaviors expressed by an animal, motor neurons are exposed to a large number and variety of modulating synaptic inputs and have evolved into subtypes with specific functions. In this thesis, motor neuron subtypes and the synaptic input to motor neurons from Renshaw cells and Ia afferents have been studied. Novel molecular markers that identify subtypes of motor neurons are described. Three markers, Chodl, Calca and ERRβ, have been used to study the degeneration of subtypes of motor neurons in a mouse model of the neurodegenerative disease amyotrophic lateral sclerosis (ALS). Another marker, 5-ht1d, has been used to record the electrophysiological character of gamma motor neurons. In mice that lack 5-ht1d, motor neurons develop with reduced proprioceptive input. Remarkably, these mice had fewer foot faults than control animals when challenged to cross a narrow beam suggesting that the amplitude of monosynaptic proprioceptive input to motor neurons is not essential for motor coordination. In a final set of experiments, genetic removal of vesicular transport of neurotransmitter from Renshaw cells suggest that Renshaw cells are not integral for motor circuit function or motor behaviors. However, they are involved in the development of motor circuits in the spinal cord. Together, this thesis provides novel molecular tools for studies of motor neuron subtypes and novel data regarding the development and function of spinal motor circuits.
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Zim, Bret E. "Improved Fabrication and Quality Control of Substrate Integrated Microelectrode Arrays." Thesis, University of North Texas, 2000. https://digital.library.unt.edu/ark:/67531/metadc2484/.
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Spontaneously active monolayer neuronal networks cultured on photoetched multimicroelectrode plates (MMEPs) offer great potential for use in studying neuronal networks. However, there are many problems associated with frequent, long-term use of MMEPs. The major problems include (1) polysiloxane insulation deterioration and breakdown, (2) and loss of gold at the gold electroplated indium-tin oxide (ITO) electrodes. The objective of this investigation was to correct these major problems. Quality control measures were employed to monitor MMEP fabrication variables. The phenotypes of polysiloxane degradation were identified and classified. Factors that were found to contribute most to insulation deterioration were (1) moisture contamination during MMEP insulation, (2) loss of the quartz barrier layer from excessive exposure to basic solutions, and (3) repetitive use in culture. As a result, the insulation equipment and methods were modified to control moisture-dependent insulation deterioration, and the KOH reprocessing solution was replaced with tetramethylguanidine to prevent damage to the quartz. The problems associated with gold electroplating were solved via the addition of a pulsed-DC application of gold in a new citrate buffered electroplating solution.
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Picado, Ricardo Migueis. "Controle semi-ativo em suspensões automotivas." [s.n.], 1998. http://repositorio.unicamp.br/jspui/handle/REPOSIP/264369.
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Orientador: Pablo Siqueira MeirellesDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica
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Resumo: Neste trabalho, será feito um estudo dos principais tipos de suspensões semi-ativas propostas até o presente. A viabilidade (econômica) de um sistema de suspensão semi-ativa depende da rapidez do algorítmo de controle, da capacidade de processamento do hardware disponível e dos custos para instalação e manutenção da suspensão. Para mostrar como estes fatores influenciam na concepção de um sistema de suspensão automotiva, foram reunidos vários algoritmos de controle e um método alternativo de controle semi-ativo baseado em redes neurais artificias foi proposto
Abstract: In this thesis, it was developed a study of the principal sorts of semi-active car suspensions. The possibility of a semi-active suspension system depends on the costs envolved, the hardware available, and the control algorithm. To show how this subjects influence the conception process of a car suspension, we compiled some algorithms and proposed an altemative one based in artificial neural networks
Mestrado
Mestre em Engenharia Mecânica
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Ribeiro, Pleycienne Trajano. "Modelagem e controle de unidades de craqueamento catalitico - FCC." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266266.
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Orientador: Rubens Maciel FilhoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica
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Resumo: Por representar um importante processo de conversão da indústria petroquímica, o craqueamento catalítico é um dos processos de conversão mais estudados. Nele, moléculas de alto peso molecular são quebradas em moléculas com menor peso molecular, obtendo-se assim produtos economicamente mais desejáveis. Os estudos do processo, de sua modelagem matemática e dos seus sistemas de controle, podem garantir o conhecimento necessário para alcançar condições operacionais ótimas que levem à máxima conversão da carga. Neste contexto, este trabalho teve como objetivos: a pesquisa e utilização de uma modelagem matemática para o conversor FCC (Fluid Catalytic Cracking); o estudo do processo sob influência de um controlador PID clássico, muito utilizado em refinarias; a estruturação de uma rede neural artificial (RNA) e o seu posterior uso como modelo interno de um controlador avançado tipo preditivo desenvolvido a partir dos estudos feitos no processo de craqueamento catalítico. Em paralelo, foi cirada uma ferramenta de simulação que possibilitou o meio mais amigável e prático para realização de todas as simulações necessárias para o desenvolvimento do presente trabalho. O FCCGUI (Fluid Catalytic Cracking Graphical User Interface), nome dado ao simulador, proporciona a escolha de parâmetros de simulação, diferentes estruturas de controle (PID, DMC e MPC - baseado em redes neurais), a visualização de diferentes variáveis manipuladas, controladas e sinais de válvulas e facilidades para perturbar o sistema. Através das simulações foi possível acompanhar o comportamento das variáveis de processo em diferentes condições testadas, realizar a estruturação da rede neural e obter as respostas das variáveis controladas para os dois tipos de controladores estudados. Os resultados obtidos foram bastante satisfatórios, visto que a modelagem matemática escolhida representa bem o sistema e o controlador MPC-Neural desenvolvido se mostrou eficiente, por conseguir manter o processo estável e próximo ao set point, mesmo após a aplicação de perturbações no processo
Abstract: Catalytic cracking is one of the most studied conversion processes due its importance in the petrochemical industry. In this process high weight molecules are broken into lighter ones, yielding more economically valuable products. The study about the process, its mathematical modeling, and its control systems may guarantee the necessary knowledge needed to reach optimal operational conditions which lead to maximum load conversion. In this context, the present work thesis has as main objectives the research and use of a mathematical modeling for a FCC (Fluid Catalytic Cracking) conversion unit, the study of the system under PID control loop widely used in refineries, structuring of an artificial neural network (ANN) with its use as an internal model of a predictive control system developed for catalytic cracking. Parallel to this, it was developed a computational tool which in a friendly and practical way made possible to carry out simulations needed to accomplish this work. FCCGUI (Fluid Catalytic Cracking Graphical User Interface), name given to this simulator, allows to choose simulation parameters, different control systems (PID, DMC, and MPC-ANN Based), graphical visualization of many different variables, such as manipulated and controlled variables plus valve signals, also it allows for and easy means for disturbing the system while the simulation continues. Through the simulations it was possible to follow the behavior of many process variables under different tested operational conditions, to structure the neural network, and to obtain controlled variables responses for both types of control systems studied. The obtained results were quite satisfactory since the chosen mathematical modeling represents well the system and the developed MPC-ANN controller showed to be efficient to maintain the process stable and close to the set points even after the introduction of disturbances in the process. Taking all these into account, compared to PID controller, MPC-ANN showed to be less oscillatory and to be more effective
Mestrado
Desenvolvimento de Processos Químicos
Mestre em Engenharia Química
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Garrido, Charles Aida. "Optical control of endogenous receptors and cellular excitability with light." Doctoral thesis, Universitat de Barcelona, 2020. http://hdl.handle.net/10803/668383.
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Light-controlled manipulation of neuronal activity has transformed the field of neurobiology. Light provides temporal and spatial resolution over activation or inhibition of targeted populations of neurons, one single neuron or single synapses. Such precision could be achieved with optogenetics, which is based on the over-expression of light-sensitive proteins, but it requires gene therapy and often alters cellular physiology. An alternative to optogenetics is offered by photopharmacology (the development of light-regulated drugs or photoswitches), which can operate on endogenous receptors without genetic manipulation. Several new photoswitches are described in this thesis to improve their pharmacological and optical properties.
In photopharmacology, azobenzene is the most commonly used light switch. Photoswitchable tethered ligands (PTLs) are tri-modular molecules able to anchor to target receptors and alter their function by switching the azobenzene group. In the first chapter we demonstrate the ability to target endogenous receptors of hippocampal neurons and olfactory bulb neurons from Xenopus larvae. The chemical strategy used was to introduce a highly reactive anchoring group to a PTL with similar structure to the reported MAG compound used in the light regulated glutamate receptor, LiGluR. These new kind of PTLs were called “Targeted Covalent Photoswitches” (TCPs).
The promiscuity of the reactive group of TCP limits the possibility to spatially confine the drug conjugation. Thus, we designed a photolabile TCP that can be conjugated to its target with a specific wavelength, and then be photoswitched at another wavelength.
Despite the advantages of all molecules described above, they share a common limitation: the activation wavelength of azobenzene is in the UV-violet range. Increasing the push-pull effect at the azobenzenic core by adding different substituents, we achieved a TCP derivative activatable at the visible range and ultrafast relaxing. In this way a single wavelength of stimulation can be used. Both features make them great candidates to control ultrafast neurotransmission processes such as the ones implicated in sound coding in the cochlea. We demonstrated in a gerbil animal model the capacity of this blue-activated TCP to photosensitize native receptors of adult gerbil cochlea. This first proof of concept opens new possibilities to develop optical cochlear implants for the treatment of hearing loss avoiding gene therapy.
Chemical substitutions can also be rationally designed to enhance two-photon (2P) absorptivity without modifying the dynamics of photoswitches. In the third chapter we described two new 2P enhanced MAG derivatives to photocontrol LiGluR. We validated their properties with an all-optical approach, by recording calcium induced neuronal responses in organotypic hippocampal slices, and in vivo in Caenorhabditis elegans. The combination of slow relaxation lifetime and enhanced 2P absorptivity is translated into an accumulation of the active isomer of the photoswitch that successfully enhances its functional effect even at low illumination power.
Another way to spectrally modify the characteristics of a chromophore while avoiding mutation screening and new synthetic processes is by using light-harvesting fluorophores. Spectral overlapping of fluorophore emission and chromophore absorption broadens its activation spectrum. By means of chemical protection and deprotection, we orthogonally control the conjugation of fluorophores and photoswitches. This is the first demonstration of light-harvesting strategy for optogenetics and photopharmacology.
Finally, we describe the use of novel PCLs containing chromophores other than linear azobenzene for the light-controlled activation of hippocampal neurons. Cyclic azobenzenes reverse isomer thermal stability and consequently also the activity of the photoswitch. On the other hand, stilbenes allow the irreversible but non-photo-destructive activation of the original molecule, thus avoiding the creation of photo-products.
In conclusion, this thesis puts forward several advances in the photochromism and pharmacology of photoswitches for the control of neurotransmission without need of genetic manipulation.L'estudi electrofisiològic i d’imatge de l’activitat neuronal en temps real requereix una gran resolució espacial i temporal. Ambdós trets es poden aconseguir amb la precisió, velocitat i control remot que permet la llum. En aquesta tesi es descriu la caracterització de nous fotocommutadors dirigits a fotosensibilitzar receptors endògens de glutamat i estratègies per la millora de les seves característiques òptiques. Els primers fotoconmutadors descrits capaços de controlar amb llum l’activitat de canals endògens de glutamat son eficaços en altres aproximacions experimentals com ara en la inducció amb llum de potencials d’acció en neurones en cultiu, en cultius organotípics d’hipocamp de rata o in vivo en larves de Xenopus electroporades, a nivell d’un grup neuronal, d’una única neurona o d’una única espina sinàptica. Modificant la part reactiva del fotocommutador, som podem controlar espacialment la conjugació mitjançant patrons d’il·luminació. Canviant l’estructura química s’aconsegueix un fotocommutador actiu en el rang visible de llum i alhora extremadament ràpid. Fet que el fa ideal pel control de sinapsis ultra ràpides com ara les encarregades de codificar el so en la còclea. El disseny racional d’altres modificacions químiques en fotocommutadors de receptors de glutamat (LiGluRs) obre les portes al disseny de molècules sensibles a l’activació per 2 fotons. L’estimulació de 2 fotons amb làsers polsats de llum infraroja comporta importants avantatges com ara l’augment de la capacitat de penetració en teixit i una disminució de possibles danys degut a una sobreexposició a la llum. Característiques molt útils per estudis in vivo. Modificacions químiques dels fotocommutadors comporten altres modificacions en les seves característiques fotodinàmiques. Per aquest motiu, hem desenvolupat una estratègia de conjugació de fluoròfors col·lectors de llum que mitjançant RET transfereixen la seva energia al cromòfor (fotocommutador), modificant-ne les característiques espectrals. Es demostra que cromòfors no conjugables permeten controlar l’activitat neuronal. Amb diversos avantatges respecte l’azobenzè clàssic: els azobenzens cíclics reverteix l’estabilitat i en conseqüència l’activitat de la molècula; i els estilbens permeten l’activació irreversible però no foto-destructiva de la molècula original, evitant així la creació de foto-productes. En conclusió, en aquesta tesi es presenten noves molècules i estratègies de disseny per al control de la neurotransmissió sense necessitat de modificacions genètiques.
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Gabriel, Filho Oscar. "Contribui??es ? an?lise de robustez de sistemas de controle usando redes neurais." Universidade Federal do Rio Grande do Norte, 2004. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15178.
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Previous issue date: 2004-03-05This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented
Este trabalho utiliza as Redes Neurais Multicamadas - RNM s, totalmente com treinamento em tempo real (on-line), no desenvolvimento de duas estrat?gias de controle indireto. Os esquemas propostos denominam-se Controle H?brido Indireto e Controle Neural Indireto. Todo o treinamento dos neurodispositivos - o identificador da planta e o controlador, quando presentes na malha de controle indireto, ? realizado com um m?nimo de atraso computacional, de modo a contemplar o controle de plantas com pequenos per?odos de amostragem. S?o apresentados Teoremas de Estabilidade para garantia da converg?ncia dos dispositivos neurais, assim como foram feitas considera??es para adequar o m?todo de acelera??o da converg?ncia h-adaptativo utilizado ?s condi??es de estabilidade. Para cada esquema de controle indireto foi desenvolvido um teorema que permite calcular o m?ximo erro permanente (steady-state error) que poder? ocorrer em fun??o da toler?ncia previamente especificada para converg?ncia dos dispositivos neurais usados na malha de controle, desde que a estabilidade seja garantida. Estes teoremas foram denominados de Teoremas da Robustez e constituem a principal contribui??o deste trabalho. As condi??es de estabilidade e robustez foram testadas para as estrat?gias de Controle H?brido Indireto e de Controle Neural Indireto, sendo apresentados os resultados obtidos na simula??o computacional do controle de regula??o de plantas n?o-lineares, BIBO (Bounded Input, Bounded Output) est?veis
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Vieira, William Gonçalves. "FCC : controle preditivo e identificação via redes neurais." [s.n.], 2002. http://repositorio.unicamp.br/jspui/handle/REPOSIP/267590.
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Orientadores: Ana Maria Frattini Fileti, Florival Rodrigues de CarvalhoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica
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Resumo: A unidade de Craqueamento Catalítico em Leito Fluido - FCC, modelo Kellogg Orthoflow F., representa um processo de refino de petróleo apresentando característica altamente não linear, possuindo fortes interaçães entre as variáveis de produção, e condições de operação extremamente severas. Essas unidades são constituídas basicamente de duas seções: uma de reação catalítica na qual ocorrem as reações de quebra de cadeia hidrocarbônica e também há formação de coque, desativando o catalisador; e outra seção onde ocorre a regeneração do catalisador desativado. O objetivo dessa unidade é transformar produtos de elevado peso molecu1ar, que apresentam baixo valor agregado, em compostos de elevado valor comercial. As unidades FCC, devido às condições severas de operação, necessitam de um controle rigoroso de determinadas variáveis operacionais. Apesar de existirem instalados controladores avançados baseados em modelos de convolução, fteqüentemente essas unidades são reguladas por meio de controladores PID padrões e também através de controle manual baseado no conhecimento de operadores das refinarias. O presente estudo tem como objetivo desenvolver um controlador preditivo multivariável (Multivariable Predictive Control - MPC) para ser implementado na unidade FCC, utilizando Redes Neurais Artificiais (RNA) como modelo interno do controlador. Inicialmente é previsto realizar a identificação do processo da FCC em RNA, obedecendo a seguinte estratégia: usando um modelo fenomenológico que representa a unidade industrial, e partindo de um estado inicial são aplicados diversos degraus nas variáveis manipuladas analisando as respostas nas variáveis controladas do processo. A partir destas simulações são gerados diversos conjuntos de dados divididos em grupos de treinamento, validação e teste. Diversas redes neurais do tipo multicamada feedforward são então criadas para representar o modelo fenomenológico, sendo selecionada aquela que apresenta melhor desempenho, quando comparada com o modelo. A configuração da RNA escolhida como modelo interno foi 8x15x4 (camadas de entrada, escondida e de saída, respectivamente) apresentando um erro relativo máximo de 1% quando comparado com os resultados do modelo rigoroso. Posteriormente, foi previsto desenvolver um controlador preditivo multivariável usando como modelo interno esta rede selecionada. Este controlador foi implementado dentro da rotina do modelo fenomenológico, sendo então realizados testes para verificar seu desempenho, comparando o resultado com o sistema aberto e também com o controlador DMC (Dynamic Matrix Contro!) existente. Diversos horizontes de predição e controle foram analisados, sendo selecionados aqueles que apresentaram melhor desempenho. Foi introduzido um ruído nos sinais do modelo fenomenológico para testar a robustez do controlador proposto. O controlador apresentou bom desempenho mesmo na presença de ruídos de 1,5%, levando sempre as variáveis controladas para seus valores de referência, o que comprova sua robustez. Baseados nestes resultados, conclui-se que um controlador preditivo multivariável baseado em RNA é perfeitamente capaz de controlar um sistema não linear de porte do FCC, onde elevada interação entre suas variáveis operacionais e fortes restrições estão presentes. Isto nos permite extrapolar que são boas as expectativas para uma futura utilização na unidade industrial, principalmente devido à sua simplicidade, robustez e facilidade de implementação, a despeito da dificuldade de sintonia do controlador
Abstract: The Fluid Cracking Catalytic unit - FCC, Kellogg Orthotlow F. model, represents a very strong nonlinear process, with severe interactions among the process variables, and extremely severe operation conditions. The unit is composed of two sections: one is the catalytic reaction, where the hydrocarbon breaks chain reactions and coke deposition take place becoming the catalyst inactive, and the other where the catalyst regeneration happens. The objective is to transform products derived ITom petroleum, with high molecular weight and low added value, into products with higher profit. Due to the severe operation conditions, rigorous control of some variable is needed. In spite of the existence of advanced control based on a convolution model, in practice, FCC units are ftequently regulated by standard PID controllers, and also through manual control actions based on the knowledge of the refinery operators. The objective of this study is to develop a Multivariable Predictive Control (MPC) to be implemented in the FCC unit, using the Artificial Neural Networks (ANN) as internal model. Initially, the process identification in ANN of the FCC was done by the following strategy: an initial state was fust achieved using numerical simulations based on the phenomenological mo deI. Then, several steps changes were applied to the manipulated variables and the response in the controlled variables were monitored and recorded. From these simulations, several groups of data were generated for training, validation and testing. The Neural Network of multilayer feedforward type were created to represent the phenomenological model, being selected the one that better represents the phenomenological model. The ANN configuration chosen to be the internal model was 8x15x4 (Input x Hidden x Output) architecture, with a maximum relative error below 1 % when comparing the results with the phenomenological model results. Later on, it was developed a multivariable predictive control based on this internal model. This control was implemented inside the routine of the phenomenological model. The performance tests were evaluated comparing the results with the open system and with the Dynamics Matrix Control (DMC). Several prediction and control horizons were analyzed. The ANN control presented good performance even in the presence of noise of 1,5% of intensity, taking back the controlled variables to its setpoints, proving its robustness. Based on these results, a multivariable predictive control based on ANN showed be perfectly able to control a nonlinear system like a FCC unit, where high interactions among process variables, and strong restriction conditions exists. This allows us to have good expectations for a future use in the industrial unit, mainly due to its simplicity, robustness and facility ofuse, in spite ofthe difliculty oftune control
Doutorado
Sistemas de Processos Quimicos e Informatica
Doutor em Engenharia Química
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Gonçalves, João Bosco. "Desenvolvimento de um sistema de controle adaptativo e integrado para locomoção de um robo bipede com tronco." [s.n.], 2004. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263888.
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Orientador: Douglas Eduardo ZampieriTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica
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Resumo: Este trabalho concebeu um robô bípede composto por uma sucessão de elos rígidos interconectados por 12 articulações rotativas, permitindo movimentos tridimensionais. O robô bípede é constituído por dois subsistemas: tronco e membros inferiores. A modelagem matemática foi realizada em separado para cada um dos subsistemas, que são integrados pelas forças reativas de vínculo. Nossa proposta permite ao robô bípede executar a andadura dinâmica utilizando o tronco para fornecer o balanço dinâmico (estabilidade postural). De forma inédita, foi desenvolvido um gerador automático de trajetória para o tronco que processa as informações de posições e acelerações impostas aos membros inferiores, dotando o robô bípede de reflexos. Foi desenvolvido um gerador de marcha que utiliza a capacidade do robô bípede de executar movimentos tridimensionais, implicando andadura dinamicamente estável sem a efetiva utilização do tronco. O gerador automático de trajetória para o tronco entra em ação se a marcha gerada não mantiver o balanço dinâmico, restabelecendo uma marcha estável. Foi projetado um sistema de controle adaptativo por modelo de referência que utiliza redes neurais artificiais. A avaliação de estabilidade é feita segundo o critério de Lyapunov. O sistema de controle e o gerador automático de trajetórias para o tronco são integrados, compondo os mecanismos adaptativos desenvolvidos para solucionar o modo de andar dinâmico
Abstract: The main objective of this work is to project a biped robot machine with a trunk. The mathematical model was realized by considering two sub-systems: the legs and the trunk. The trajectories of the trunk are planned to compensate torques inherent to the dynamic gait, permitting to preserve the dynamic balance of the biped robot. An automatic generator of trajectory for the trunk was developed that processes the infonnation of positions and accelerations imposed to the legs. A gait generator was developed that uses the capacity of the biped robot to execute three-dimensional movements, causing a steady dynamic gait without the effective use of the trunk. The automatic generator of trajectory for the trunk actuates, if the generated do not keep the dynamic balance, reestablishing he steady dynamic gait. A neural network reference model for the adaptive control was projected, which utilizes an RBF neural network and a stability evaluation is based on the criterion of Lyapunov. The system of control and the automatic generator of trajectories for the trunk are integrated, composing the adaptive mechanisms developed to solve the way of dynamic walking
Doutorado
Mecanica dos Sólidos e Projeto Mecanico
Doutor em Engenharia Mecânica
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Gervini, Vitor Irigon. "Modelagem e controle de um servoposicionador pneumático via redes neurais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/110080.
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Visando apoiar o desenvolvimento de controladores para servoposicionadores pneumáticos, é apresentada no presente trabalho uma proposta de um procedimento baseado no uso de redes neurais para a determinação de modelos matemáticos precisos que possam ser aplicados tanto para a simulação do seu comportamento dinâmico quanto na estrutura de controladores que utilizam estratégias baseadas em modelos. No âmbito do trabalho, esse procedimento foi testado por meio de sua aplicação na identificação das forças de atrito e da relação pressão/vazão mássica nos orifícios de controle da servoválvula (que consistem nas principais não-linearidades envolvidas em tais sistemas). Além disso, determinou-se através de redes neurais a relação inversa entre as vazões desejadas e o sinal de controle da servoválvula (difeomorfismo), a qual é aplicada em técnicas de controle baseadas em modelos. Visando validar o procedimento de modelagem proposto, foram realizadas simulações em malha aberta e malha fechada, cujos resultados são comparados com os de experimentos realizados em uma bancada de testes. Com o intuito de comprovar sua eficácia em aplicações de controle, o modelo baseado em redes neurais foi utilizado no desenvolvimento de um controlador não-linear sintetizado de acordo com uma estratégia em cascata (a qual foi já testada em outros trabalhos, mostrando resultados satisfatórios quando aplicada ao controle de servoposicionadores pneumáticos). No entanto, essa estratégia apresenta dificuldades de implantação em decorrência das dificuldades associadas ao processo de identificação dos parâmetros do sistema, que são especialmente trabalhosos neste caso. As características de estabilidade em malha fechada foram analisadas por meio do segundo método Lyapunov. Os resultados experimentais em malha fechada obtidos atestam a eficácia da estratégia de controle proposta.The development of a precise positioning system has motivated several researches in the pneumatic systems control area to overcome the problems caused by these nonlinearities, by appropriate feedback control algorithms. In this work it is proposed a methodology based on neural networks to achieve accurate mathematical models that can be used in simulation as in controllers techniques based on models. This methodology was tested through its application in identifying the phenomenon of friction and the relationship pressure/mass flow through servo valve orifices control holes. Furthermore, using neural networks, the inverse relationship between the desired flow rates and control signal of servo valve (diffeomorphism), which is applied in various control techniques based on models, was determined. To evaluate the proposed modeling methodology, simulations were done in open and closed loop, and the results were compared with experiments conducted on a real pneumatic servo positioning system. A neural network based model was used to develop a nonlinear controller according to a cascade strategy with friction compensation (which has been tested on other studies showing satisfactory results when applied to pneumatic servo positioning control). The cascade control strategy, despite showing a good performance in trajectory tracking, presents significant difficulties in implementation due mainly to difficulties associated with the system parameters identification process, which are especially expensive. The characteristics of the closed loop stability were analyzed by Lyapunov method. The experimental results obtained in closed loop attest the efficiency of the proposed control strategy.
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Lucena, Pedro Berretta de. "An?lise de um controlador baseado no Jacobiano estimado da planta atrav?s de uma rede neural." Universidade Federal do Rio Grande do Norte, 2005. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15399.
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Previous issue date: 2005-12-16This work presents an analysis of the control law based on an indirect hybrid scheme using neural network, initially proposed for O. Adetona, S. Sathanathan and L. H. Keel. Implementations of this control law, for a level plant of second order, was resulted an oscillatory behavior, even if the neural identifier has converged. Such results had motivated the investigation of the applicability of that law. Starting from that, had been made stability mathematical analysis and several implementations, with simulated plants and with real plants, for analyze the problem. The analysis has been showed the law was designed being despised some components of dynamic of the plant to be controlled. Thus, for plants that these components have a significant influence in its dynamic, the law tends to fail
Este trabalho apresenta uma an?lise da lei de controle baseada em um esquema h?brido indireto usando rede neural, proposto inicialmente por O. Adetona, S. Sathanathan e L. H. Keel. Implementa??es dessa lei de controle, para uma planta de n?vel de segunda ordem, resultaram em um comportamento oscilat?rio, mesmo com a converg?ncia do identificador neural. Tais resultados motivaram a investiga??o da aplicabilidade dessa lei. A partir disso, foram feitas an?lises matem?ticas de estabilidade e diversas implementa??es, com plantas simuladas e com plantas reais, com a finalidade de se analisar o problema. A an?lise mostrou que a lei foi desenvolvida desprezando-se certos componentes da din?mica da planta a ser controlada. Sendo assim, para plantas onde esses componentes t?m uma influ?ncia significativa em sua din?mica, a lei tende a falhar
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Maeland, Jahn Andreas. "Model-reference neural control." Thesis, University of Salford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238757.
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Ismael, Ali. "Neural adaptive control systems /." free to MU campus, to others for purchase, 1998. http://wwwlib.umi.com/cr/mo/fullcit?p9901244.
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Caporali, Alexandre Simião. "Estratégias de controle não-convencional para uma plataforma de Stewart acionada hidraulicamente." Universidade de São Paulo, 2003. http://www.teses.usp.br/teses/disponiveis/18/18135/tde-16022016-121810/.
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Este trabalho apresenta técnicas de projeto de controle neural e controle difuso para uma plataforma de Stewart acionada hidraulicamente. O modelo dinâmico não linear da plataforma de Stewart com seis graus de liberdade foi desenvolvido no ambiente de sistemas multicorpos ADAMS. Este pacote comercial foi usado para economizar tempo e esforço na modelagem de um sistema mecânico complexo e na programação para obter a resposta no tempo do sistema. A plataforma de Stewart é um manipulador paralelo com alta relação força-peso e acuracidade de posicionamento comparada a manipuladores seriais convencionais. As desvantagens dos mecanismos seriais é que cada articulação suporta o peso da articulação seguinte e mais o objeto a ser manipulado. A plataforma de Stewart tem recebido recentemente considerável interesse de pesquisadores dado o sucesso de suas aplicações e potencial vantagens sobre os manipuladores convencionais. Uma aplicação bastante popular da plataforma de Stewart é o simulador de vôo onde a plataforma executa movimento com acelerações similares àquelas de uma aeronave. Embora muitas pesquisas na literatura tenham dedicado amplo esforço para cinemática, dinâmica e projeto mecânico de manipuladores baseados em plataforma de Stewart, pouca atenção tem sido dada ao problema de controle deste tipo de manipulador. Um esquema de controle difuso e de redes neurais foi adotado para lidar com as não linearidades, distúrbios e incertezas dos parâmetros, e precisão necessária no posicionamento e orientação da plataforma. Redes neurais artificiais e lógica difusa fornecem um paradigma computacional característico e tem demonstrado resultado para uma faixa de problemas práticos onde a técnica computacional convencional não tem sucesso. Em particular, a habilidade do controle neural e do controle difuso para representar mapeamento não linear encoraja o estudo de controle neural e difuso para representar problemas de controle não linear. Resultados de simulação são apresentados, mostrando que as técnicas propostas podem ser usadas na plataforma de Stewart.This work presents a neural and fuzzy control design technique for a hydraulically driven Stewart platform. The non-linear dynamic model of a Stewart platform with six degrees of freedom was developed in the multibody systems environment ADAMS. This commercial package was used to save time and effort in modelling the complex mechanical system and in the programming to get the time response of the system. The Stewart platform is a parallel manipulator with high force-to-weight ratio and position accuracy compared to conventional serial manipulators. The disadvantage of serial mechanisms is that each link has to support the weigth of all the following links in addition to the object to be supported. The Stewart platform has recently received considerable research interest due to its successful applications and potential advantages over the conventional manipulators. A quite popular application of the Stewart platform is the flight simulator where the platform performs motion with accelerations similar to those of an airplane. Although much of the research in the literature has devoted extensive effort to the kinematics, dynamics and mechanisms design of the Stewart platform-based manipulators, little attention has been paid to the control problem of this type of manipulators. A fuzzy and neural network control scheme was adopted to deal with the nonlinealities, disturbances and uncertainties of the parameters, and required precision in position and orientation the platform. Artificial neural networks and fuzzy logic provide a distinctive computational paradigm and have proven to be effective for a range of practical problems where conventional computation techniques have not succeeded. In particular, the ability of neural and fuzzy control techniques to represent non-linear mappings encourages the study of these techniques to be used for controling complex non-linear control problems. Simulations results are presented, showing that the proposed technique can be used in a Stewart platform.
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Pazelli, Tatiana de Figueiredo Pereira Alves Taveira. "Controladores adaptativos não-lineares com critério H \'INFINITO\' aplicados a robôs espaciais." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-26022007-152250/.
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Neste trabalho, o equacionamento dinâmico de um manipulador espacial de base livre flutuante é descrito a partir do conceito do manipulador dinamicamente equivalente para que as técnicas de controle desenvolvidas sejam experimentalmente validadas em um manipulador convencional de base fixa. Dois tipos de controle de movimento são considerados. O primeiro foi desenvolvido no espaço das juntas e realiza o comando direto de posicionamento das juntas do manipulador; o segundo foi desenvolvido no espaço inercial e o controle é direcionado para o posicionamento do efetuador no espaço Cartesiano. Nos dois casos, o problema de acompanhamento de trajetória de um manipulador espacial com base livre flutuante sujeito a incertezas na planta e perturbações externas é proposto e solucionado sob o ponto de vista do critério de desempenho H \'INFINITO\'. Considerando métodos de controle para sistemas subatuados, três técnicas adaptativas foram desenvolvidas a partir de um controlador H \'INFINITO\' não-linear baseado na teoria dos jogos. A primeira técnica foi proposta considerando a estrutura do modelo bem definida, porém calculada com base em parâmetros incertos. Uma lei adaptativa foi aplicada para estimar esses parâmetros utilizando parametrização linear. Redes neurais artificiais são aplicadas nas outras duas abordagens adaptativas. A primeira utiliza uma rede neural para aprender o comportamento dinâmico do sistema robótico, considerado totalmente desconhecido. Nenhum dado cinemático ou dinâmico da base é utilizado neste caso. A segunda abordagem considera a estrutura do modelo nominal do manipulador bem definida e a rede neural é aplicada para estimar o comportamento das incertezas paramétricas e da dinâmica não-modelada da base. O critério H \'INFINITO\' é aplicado nas três técnicas para atenuar o efeito dos erros de estimativa. Resultados experimentais foram obtidos com um robô manipulador de base fixa subatuado (UArmII) e apresentaram melhor desempenho no acompanhamento da trajetória e no consumo de energia para as abordagens baseadas em redes neurais.In the present work, the dynamics of a free-floating space manipulator is described through the dynamically equivalent manipulator approach in order to obtain experimental results in a planar fixed base manipulator. Control in joint and Cartesian spaces are considered. The first acts directly on joints positioning; the second control scheme acts on positioning the end-effector in some inertially fixed position. In both cases, the problem of tracking control with a guaranteed H-infinity performance for free-floating manipulator systems with plant uncertainties and external disturbances is proposed and solved. Considering control methods for underactuated systems, three adaptive techniques were developed from a nonlinear H-infinity controller based on game theory. The first approach was proposed considering a well defined structure for the plant, however it was computed based on uncertain parameters. An adaptive law was applied to estimate these parameters using linear parametrization. Artificial neural networks were applied in the two other approaches. The first one uses a neural network to learn the dynamic behavior from the robotic system, which is considered totally unknown. No kinematics or dynamics data from the spacecraft are necessary in this case. The second approach considers the nominal model structure well defined and the neural network is applied to estimate the behavior of the parametric uncertainties and of the spacecraft non-modeled dynamics. The H-infinity criterion was applied to attenuate the effect of estimation errors in the three techniques. Experimental results were obtained with an underactuated fixed-base planar manipulator (UArmII) and presented better performance in tracking and energy consumption for the neural based approaches.
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Gonzaga, João Carlos Bastos. "Desenvolvimento de procedimento e Soft-Sensors para controle de plantas de PET." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266832.
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Orientador: Rubens Maciel FilhoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química
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Resumo: Neste trabalho são apresentados três estudos distintos de aplicação de Plantwide Control. A primeira aplicação trata-se de um controle antecipativo (feedforward) para controlar os níveis dos reatores na etapa de polimerização, a fim de reduzir suas variabilidades e, consequentemente, a produção de refugo, sendo que, em uma planta de Politereftalato de Etileno (PET), a variação de nível dos polimerizadores interfere na viscosidade e está diretamente relacionada com a capacidade e com a qualidade de produção. A segunda aplicação mostra como desenvolver e utilizar um modelo computacional da planta de PET para possibilitar que alterações de parâmetros de processo, como temperatura e pressão, possam ser feitas sem que haja a necessidade de testes na planta real, uma vez que a existência de um modelo computacional que tenha o mesmo comportamento qualitativo da planta real permite que o efeito de perturbações e outros tipos de alterações na condição do processo sejam avaliados. A terceira aplicação trata-se da implantação de um sensor virtual (soft-sensor), utilizando redes neurais artificiais (RNA) para atuar como um medidor redundante da viscosidade, podendo substituir o sensor físico no caso deste vir a falhar. Estes estudos têm em comum a apresentação de procedimentos para controle do processo de produção de PET, que por possuir muitas particularidades, torna-se um assunto complexo, sendo um desafio modelar e controlar cada única unidade de produção
Abstract: In this work are presented three separate studies of application of Plantwide Control. The first application is a feedforward control to control the levels of reactors in polymerization step, in order to reduce their variability and, consequently, the production of waste, because, in a plant of PET, the variance of level of polymerizing interferes in viscosity and is directly related to the capacity and quality of production. The second application shows how to develop and use a computational model of a PET plant to enable changes to process parameters such as temperature and pressure, without the need of tests in actual plant, once the existence of a computational model has the same qualitative behavior of actual plant, and it allows the effect of disturbance and other types of changes in the condition of the process to be evaluated. The third application is the implantation of a virtual sensor (soft-sensor), using RNA, to act as a redundant viscosity meter that, in the case of possible failures, has as main function to detect physical sensor failures and replace it in the control system monitoring. Generally, the three studies have in common the presentation of procedures to control the production process of polyester. Process control for the production of polymers presents many particularities and, therefore, becomes a complex matter, being a challenge to model and to control every single production unit
Doutorado
Desenvolvimento de Processos Químicos
Doutor em Engenharia Química
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Grassi, Luiz Henrique Maricato [UNESP]. "Identificação e controle de sistemas dinâmicos utilizando redes wavelets." Universidade Estadual Paulista (UNESP), 2004. http://hdl.handle.net/11449/94538.
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grassi_lfm_me_ilha.pdf: 1030941 bytes, checksum: 1b6f71060acf49c7dfe0879c783856af (MD5)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
A necessidade de controle no tratamento de sistemas dinâmicos, com complexidade crescente e diante de fatores de incerteza, tem levado à reavaliação dos métodos convencionais e à proposição de métodos conceitualmente mais elaborados de controle. Estas novas propostas incluem, por exemplo, níveis hierárquicos de decisão, planejamento e aprendizagem, que são necessários quando um alto grau de autonomia do sistema é desejável. Assim as metodologias baseadas em redes neurais, que utilizam modelos matemáticos e técnicas numéricas inspiradas no cérebro humano e/ou sistema nervoso, representam um passo natural na evolução da teoria de controle, principalmente junto àqueles que envolvem não-linearidades. Este trabalho apresenta um estudo da técnica denominada wavenet, que combina redes neurais e transformada wavelet, como um direcionamento alternativo para a solução de problemas de identificação e controle de plantas não lineares. A transformada wavelet utiliza janelas com escala variável que possibilitam analisar faixas de altas e baixas freqüências em um mesmo sinal, e é exatamente essa capacidade de manipulação da janela de observação que a torna uma boa alternativa como função de ativação, realizando um mapeamento local do sinal. Isso proporciona uma identificação mais eficiente, principalmente em sinais não lineares e variantes no tempo. Vários testes simulados envolvendo não linearidade foram analisados visando estudar o comportamento do algoritmo wavenet e definir quais os tipos de funções de ativação, Morlet, Rasp ou Polywog, poderiam fornecer melhores resultados. Utilizou-se o método de otimização de Levenberg-Marquadt, o qual apresentou um desempenho melhor quando comparado com o método do gradiente descendente utilizado por outros autores, no processo de minimização do erro entre a saída da rede e a... .
The necessity of dynamic systems treatment control, with upper complexity and uncertain factors, has lead to reevaluation of conventional methods and the proposition of conceptly methods more elaborate of control. These new proposals include, for instance, hierarchic levels of decision, planning and learning, which are needed when a high degree of system autonomy is desirable. Thus the methodologies based in neural nets, which use mathematical models and numerical techniques inspired in human brain and/or nervous system, represent a natural step in evolution of control theory, mainly join to those which involve no-linearity. This work shows a technique study called wavenet, it combine neural nets and wavelet transformed, as an alternative leading for the solution of identification problems and non linear plants control. The transformed wavelet uses windows with variable scale and it makes possible analyze strips high and low frequencies in a same signal, and it is exactly this capacity of manipulation of observation window and it becomes a good alternative as activation function, achieving a local map of the signal. A identification more efficient is provided, mainly in non-linear signals and time variants. Several simulate tests involving non linear was analyzed, seeking to study the behavior of the algorithm wavenet and to define which the types of activation functions, Morlet, Rasp or Polywog, could give better results. The optimization method of Levenberg-Marquadt was used, and that one show a better performance when compared with the descendent gradient method used by other authors, in minimization of error process between the net and plant exit. The tests looked for to define improvements in algorithm wavenet, in relation to identification process, because it is primordial stage in the project of neurocontrolers. The... (Complete abstract, click electronic address below).
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Maduna, Tando Lerato. "Vasoactive intestinal peptide (VIP) controls the development of the nervous system and its functions through VPAC1 receptor signalling : lessons from microcephaly and hyperalgesia in VIP-deficient mice." Thesis, Strasbourg, 2017. http://www.theses.fr/2017STRAJ009/document.
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Mes études doctorales ont permis de démontrer que les souris déficientes en VIP présentent une microcéphalie ayant principalement une origine maternelle qui affecte secondairement le développement de la substance blanche. Cette production placentaire par les lymphocytes T pourrait être affectée dans des pathologies du système immunitaire. De plus, nos données indiquent qu’une déficience en VIP prédispose à l'apparition de troubles sensoriels, en particulier de la nociception. Il est donc possible que les déficits précoces de développement du cerveau murin et l'apparition de l'hypersensibilité cutanée mécanique et thermique froide soient deux facettes d'une même pathologie. Des mesures d'activité de décharge spontanée des neurones dans le thalamus sensoriel chez des mâles adultes anesthésiés ont montré que les neurones des animaux KO sont hyper-excités, ce qui suggère un traitement aberrant des informations, notamment nociceptives, ou que l'activité inhibitrice des interneurones des réseaux locaux est réduiteThe studies carried out during my PhD demonstrate that VIP-deficient mice suffer from microcephaly and as well as white matter deficits mainly due to the absence of maternal VIP during embryogenesis, Placental secretion of VIP is dependent on T lymphocytes and could be altered in pathologies of the immune system. Moreover, our data links VIP deficiency to sensory alterations, specifically, the nociceptive system. Thus, it is possible that early developmental defects and hypersensitivity to mechanical and cold stimuli are two manifestations of the same pathology. This hypothesis was reinforced following analysis of spontaneous firing patterns of neurons in the sensory thalamus of anesthetized adult males. Neurons from VIP-KO mice are hyperactive, which suggests aberrant local processing of nociceptive input or that the inhibitory inputs from local interneuron networks is reduced
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Santos, Tiago Henrique dos. "Estimador neural de velocidade aplicado a um driver de controle escalar do motor de indução trifásico." Universidade Tecnológica Federal do Paraná, 2012. http://repositorio.utfpr.edu.br/jspui/handle/1/781.
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Este trabalho propõe uma abordagem baseada em redes neurais artificiais para estimar a velocidade do motor de indução aplicado no controle escalar a laço fechado. Os motores de indução têm grande importância nos mais diversos setores industriais por sua robustez e baixo custo. Assim, quando a carga acoplada ao eixo necessita do controle de velocidade, parte das estratégias de controle e acionamento são baseadas na estimativa de velocidade do eixo do motor. A medida direta da velocidade diminui a robustez comprometendo o sistema de acionamento e controle bem como o aumento do custo de implementação. A proposta deste trabalho consiste em apresentar uma metodologia alternativa às tradicionais para estimativa de velocidade do motor de indução trifásico acionado por um inversor fonte de tensão utilizando modulação espacial vetorial na estratégia de controle escalar. Resultados de simulação e experimentais são apresentados para validar o método proposto com o motor submetido a variações de velocidade e torque de carga, os quais demostraram ser bem promissores.This work proposes an artificial neural network approach to estimate the induction motor speed applied in a closed-loop scalar control. The induction motor has a great importance in many industrial sectors for the robustness and low cost. Thus, when the load coupled to the axis needs speed control, some of the drive and control strategies are based on the estimated axis speed of the motor. The direct measurement of this quantity reduces its robustness, compromises the driver system and control as well as it increases the implementation cost. The propose of this work is to present an alternative methodology for speed estimate of three phase induction motor driven by a voltage source inverter using space vector modulation in the scalar control strategy. Simulation and experimental results are presented to validate the performance of the proposed method under motor load torque and speed reference set point variations, which show very promising.
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Eyng, Eduardo. "Controle feedforward baseado em redes neurais aplicado a coluna de absorção do processo de produção de etanol." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/267396.
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Orientadores: Ana Maria Frattini Fileti, Fernando PaluDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química
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Resumo: O etanol perdido por evaporação durante o processo de produção por fermentação pode ser recuperado por uma coluna de absorção, a qual requer um sistema de controle robusto de acordo com sua complexidade. Sendo assim, no presente trabalho foi proposto e testado, o emprego de um controlador feedforward, baseado em um modelo inverso de redes neurais, para realizar a manipulação da vazão de solvente que é alimentado a esta coluna. O desempenho do controlador feedforward proposto foi superior ao proporcionado pelo Controle por Matriz Dinâmica (DMC) (Palú, 2001), para situações nas quais uma perturbação degrau foi inserida na composição do gás à entrada da coluna. Outro teste realizado foi o de implementar um distúrbio não previsto na etapa de treinamento da rede neural, e analisar o comportamento do sistema de controle RNA. Houve uma queda de eficiência, sendo gerado off set. Para solucionar este problema, agregou-se ao sistema de controle, um dispositivo de segurança. Também se procurou testar a tolerância do sistema de controle a distorções nos dados de entrada da rede. Neste sentido, acrescentou-se às variáveis de entrada do tipo concentração, um ruído. O desempenho do controlador RNA foi prejudicado, no entanto, a faixa de oscilação da variável controlada foi reduzida à aproximadamente 50% da faixa de ruído empregada. Aplicando-se um filtro aos dados distorcidos, esta redução foi ainda maior, cerca de 75%
Abstract: Some of ethanol lost by evaporation during its fermentation production process may be recovered using an absorption column, which requires a robust control system. In this work the use of a feedforward controller (NN controller), based on a neural network inverse model, was proposed and tested to manipulate the solvent flow, which was fed in the analyzed column. The feedforward controller performance was better than the Dynamic Matrix Control (Palú, 2001) one, when step disturbances were inserted on the inlet gas composition. Another test done was the insert of a not trained disturbance. The NN controller performance decrease, and a off set could be observed. To solve this problem, a security device was added to the control system. The control system tolerance to modified input neural network data also was tested. In this way, a noise was added to input data. The NN control performance decreased, but the amplitude of the control variable oscillation band was reduced to the half of the noise amplitude employed. When the modified data was filtered the NN control performance decrease was smaller, about 75% of the noise amplitude
Mestrado
Sistemas de Processos Quimicos e Informatica
Mestre em Engenharia Química
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Sepulveda, Inostroza Francisco Antonio 1965. "Redes neurais artificiais para o controle da mancha produzida por estimilação eletrica neuromuscular." [s.n.], 1996. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260356.
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Orientador: Alberto Cliquet JuniorTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica
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Resumo: Neste Trabalho, foi explorada a aplicação de redes neurais artificiais para o controle da marcha por meio de estimulação elétrica neuromuscular em pacientes com lesão medular. Para tanto, dois caminhos independentes foram seguidos, um teórico, e outro experimental. No estudo teórico, foi preparada uma rede neural de três camadas para modelar as transformações sensório-motoras segmentares ocorridas durante a marcha num plano. As entradas para a rede neural foram proporcionais aos ângulos de flexão e extensão do quadril, joelho e tornozelo, e à componente vertical da força de reação do solo. As saídas foram proporcionais ao nível de atividade em cinco músculos essenciais à produção da marcha vista num plano sagital. Os resultados de simulações com várias estruturas neurais diferentes indicam uma melhora no controle do movimento quando a última saída é incluída no vetor de entrada atual. Além disso, o controle da marcha parece ser melhor quando executado por duas redes independentes (uma para a fase de apoio da marcha, e outra para a fase de balanço) do que quando uma única rede é usada para o controle de todo o ciclo da marcha. Por outro lado, nenhuma melhora foi observada com a inclusão de recursão no algo ritmo de aprendizado, memória de entradas passadas, intraconectividade na camada escondida, conectividade seletiva entre as camadas escondida e de saída, ou do uso de derivadas dos sinais de entrada e saída. No trabalho experimental, uma rede neural de três camadas foi usada no controle adaptativo da geração da fase de balanço. Dois sistemas foram testados. No Sistema 1, na ntrada da rede neural foram usados os sinais dos goniômetros de joelho e tornozelo elo.,Sistema 2, os ângulos do quadril e joelho foram considerados. Em ambos os casos, as saídas foram proporcionais ao aumento ou diminuição da largura de pulso aplicada. A estimulação foi aplicada no nervo femoral e no nervo peroneal comum. A rede neural foi treinada de modo 'on-line' e ?off-line'. Para avaliar o desempenho dos sistemas, varias combinações de largura de pulso foram preestabelecidas. A resposta do sistema (movimentos produzidos) foi então comparada a um ciclo de referência obtido para cada sessão de testes. O treinamento 'on-line' consistiu na aplicação de punição e reforço positivo de modo seletivo. Tanto o esquema 'off-line' como o esquema 'on-line' incluíram o uso de um algo ritmo de retropropagação acelerado. Ao comparar o desempenho dos Sistemas I e 2, o primeiro parece ser melhor. Além disso, o desempenho da rede durante o treinamento 'on-line' é melhor que o da rede treinada apenas 'off-line'. De acordo com alguns resultados, um protótipo no Sistema I foi preparado e usado na geração do ciclo completo da marcha em um paciente com lesão medular
Abstract: This work consisted in the application of artificial neural network algorithms for control of gait generated by NeuroMuscular Electrical Stimulation (EENM) in spinal cord injured subjects. Two independent approaches were attempted -namely, a theoretical, and an experimental approach. ln the theoretical study, a three-Iayered neural network was set up to modei the segmental sensorimotor transformations involved in leveI walking. Network inputs were proportional to hip, knee, and ankle flexion/extension angles, and to vertical ground reaction forces. The output signal was proportional to the activity leveI of five muscles essential to gait production as seen from the sagittal plane. Results fram simulations for various network structures indicate that motion control improves when the latest output is used as part of the input vector. AIso, it appears that motion control is better when done with two independent networks (one for the stance phase of gait and another for the swing phase) than with a single network for the entire gait cycle. Further, inclusion of explicit recursion in the learning algorithm, recall of previous inputs, hidden layer intraconnectivity, selective hidden layer to output layer connectivity, and the use of signal derivatives all resulted in r;o improvement in the simulated gait controI. ln the experimental approach, a three-Iayered artificial neural network was used for adaptive control of the swing phase only. Network inputs consisted of knee and ankle goniometer signals for System 1, and knee and hip angular data for System 2. Controller output was proportional to changes in applied NMES pulse idth (PW). Stimulation was applied to the left femoral and common peroneal nerves. The neural networks were trained off-line and on-line. Network performance was assessed by applying a number of different stimulation PWs and later comparing the resulting motion to a sample good step observed during the same test session. On-line training consisted of negative and positive re-enforcement applied at chosen times. Both on-line and off-line training algorithms included an enhanced back-propagation scheme. Performance evaluation results favour the use of System I over System 2. AIso, nerwork performance during on-line learning is better than that of a network submitted to off-line learning only. Then, according to some of the results, a prototype based on System I was set up and used for generation of the entire gait cycle in one spinal subject
Doutorado
Doutor em Engenharia Elétrica
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Krishnapura, Venugopal G. "Neural networks in process control." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq28502.pdf.
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