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Bin, Abdullah Muhammad. "Development and analysis of Predictive Functional Control for a range of dynamical processes." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/23012/.
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This thesis presents a development and analysis of a low computation Model Predictive Control (MPC) that is known explicitly as Predictive Functional Control (PFC) for different types of dynamical processes. Since the current concept of PFC suffers from several issues such as the weak efficacy of tuning parameter, conservative constrained solution and poor handling of challenging dynamical systems, the prime objective of this research is to develop novel approaches to tackle these limitations while retaining the simplicity of formulation, coding and tuning of PFC. For the first contribution, a Laguerre based PFC (LPFC) is proposed to handle a system with stable and straightforward dynamics where it can provide better consistency between model predictions and actual system behaviour. Consequently, LPFC also improves the overall closed-loop performance including the efficacy of tuning parameter while providing more accurate and less conservative constrained solutions compared to the conventional PFC. For the second contribution, a Pole Shaping PFC (PS-PFC) is developed based on the original idea of the traditional pole cancellation technique to alleviate the effect of undesirable poles when dealing with more challenging dynamical processes such as those with open-loop integrating, oscillating and unstable modes. This approach provides a stable response with less aggressive input demand compared to the pole cancellation method while retaining a similar recursive feasibility property of constraint handling. The third contribution of this research is on the development of an off-line sensitivity analysis to measure the robustness and possible sensitivity trade-off for different PFC structures in response to noise, disturbance and parameter uncertainty. The findings show that although LPFC provides better closed-loop performance than PFC, yet the control loop may become more sensitive to noise. On the other hand, for PS-PFC, since the conventional Independent Model (IM) structure is unable to handle a divergent prediction, a T-filter is proposed where it manages to recover the sensitivity to noise by sacrificing its sensitivity to disturbance and parameter uncertainty.
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Rosendahl, Erik. "Fall prediction and a high-intensity functional exercise programme to improve physical functions and to prevent falls among older people living in residential care facilities." Doctoral thesis, Umeå : Samhällsmedicin och rehabilitering Community Medicine and Rehabilitation, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-756.
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Zhang, Qin. "Estimation du couple généré par un muscle sous SEF à la base de l'EMG évoquée pour le suivi de la fatigue et le contrôle du couple en boucle fermée." Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2011. http://tel.archives-ouvertes.fr/tel-00820474.
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La stimulation éléctrique fonctionnelle (SEF) peut améliorer de manière significative la mobilité des blessés médullaires ainsi que la stabilité et la prévention des effets secondaires. Dans le domaine de la SEF pour les membres inférieurs, le couple articulaire doit être fournie de façon appropriée pour effectuer le mouvement prévu afin de maintenir l'équilibre postural. Toutefois, les changements d'état du muscle telle que la fatigue musculaire est une cause majeure qui dégrade ses performances. En outre, la plupart des patients, dont la blessure médulaire est complète, n'ont pas le retour sensorielle qui permet de détecter la fatigue. De plus, et les capteurs de couples in-vivo ne sont pas disponibles à l'heure actuelle. Les systèmes conventionnels de commande SEF sont soit en boucle ouverte ou en boucle fermée mais cependant pas assez robustes aux changements d'état du muscle. L'objectif de cette thèse est le développement de la prédiction du couple articulaire et de la commande en boucle fermée afin d'améliorer les performances de la commande SEF en termes de précision, de robustesse et de sécurité pour les patients. Afin de prédire le couple articliare induit de la SEF, l'électromyographie (EMG) induit est utilisée pour corréler l'activité musculaire éléctrique et mécanique. Bien que la fatigue musculaire représente une variation dans le temps, une dépendance aux sujets et aux protocoles, la méthode proposée d'identification adaptative, basée sur le filtre de Kalman, est capable de prédire le couple articlaire variant dans le temps de manière systématique. La robustesse de la prédiction du couple articulaire a été evaluée lors d'une tâche de suivi de la fatigue en expérimentation chez des sujets blessés médullaires. Les résultats montrent une bonne performance de suivi des variations d'état des muscles en présence de fatigue et face à d'autres perturbations. Basée sur les performances de precision de la méthode prédictive proposée, une nouvelle stratégie de commande utilisant le retour EMG, "EMG-Feedback Predictive Control (EFPC)", est proposée afin de contrôler de manière adaptative les séquences de stimulation en compensant la variation dans le temps de l'état du muscle. De plus, cette stratégie de commande permet explicitement d'éviter d'appliquer une stimulation excessive aux patients, et de générer les séquences de stimulation appropriées pour obtenir la trajectoire désirée des couples articulaires.
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Morinelly, Sanchez Juan Eduardo. "Adaptive Model Predictive Control with Generalized Orthonormal Basis Functions." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1091.
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An adaptive model predictive control (MPC) method using models derived from orthonormal basis functions is presented. The defining predictor dynamics are obtained from state-space realizations of finite truncations of generalized orthonormal basis functions (GOBF). A structured approach to define multivariable system models with customizable, open-loop stable linear dynamics is presented in Chapter 2. Properties of these model objects that are relevant to the adaptation component of the overall scheme, are also discussed. In Chapter 3, non-adaptive model predictive control policies are presented with the definition of extended state representations through filter operations that enable output feedback. An infinite horizon set-point tracking policy which always exists under the adopted modeling framework is presented. This policy and its associated cost are included as the terminal stage elements for a more general constrained case. The analysis of robust stability guarantees for the non-adaptive constrained formulation is presented, under the assumption of small prediction errors. In Chapter 4, adaptation is introduced and the certainty equivalence constrained MPC policy is formulated under the same framework of its non-adaptive counterpart. Information constraints that induce the excitation of the signals relevant to the adaptation process are formulated in Chapter 5. The constraint generation leverages the GOBF model structure by enforcing a sufficient richness condition directly on the state elements relevant to the control task. This is accomplished by the definition of a selection procedure that takes into account the characteristics of the most current parameter estimate distribution. Throughout the manuscript, illustrative simulation examples are provided with respect to minimal plant models. Concluding remarks and general descriptions for potential future work are outlined in Chapter 6.
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Boyer, Baptiste. "Optimisation des ressources dans un système énergétique complexe au moyen de modèles fonctionnels." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG033.
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Pour faire face à la complexité croissante des systèmes développés, cette thèse propose une approche méthodologique multi-vues permettant d'accompagner les étapes du cycle de développement de systèmes complexes, dont notamment les systèmes multi-énergies, depuis leur conception jusqu'à leur pilotage en temps réel. Un niveau d'arbitrage entre les différentes missions du système est également intégré et permet d'évaluer plusieurs stratégies. Ce niveau est appliqué au cas du véhicule électrique entre les missions d'autonomie, de confort et de vitesse. La méthodologie développée dans cette thèse est centrée autour de la modélisation fonctionnelle, sur laquelle ces travaux se concentrent. Celle-ci décrit de manière modulaire et au moyen de modèles mathématiques juste nécessaires et de liens énergétiques le comportement des éléments du système et leurs interactions. Afin de prendre en compte au mieux la réponse dynamique des éléments, leurs contraintes et les éventuelles perturbations, des algorithmes de commande prédictive ``PFC'' sont développés puis implémentés au sein des éléments fonctionnels. Ces algorithmes servent également de support pour l'introduction d'un problème d'optimisation pour gérer le processus d'allocation des ressources dans un système multi-sources. Ces concepts sont appliqués au pilotage d'un parc éolien couplé à une unité de stockage, avec la prise en compte de contraintes de congestion sur le réseau. Enfin, l'extension de cette méthodologie à l'optimisation des systèmes multi-énergies soulève de nouvelles problématiques, notamment le couplage entre plusieurs domaines énergétiques, la prise en compte de variables manipulables discrètes et un conflit entre la nécessité d'avoir à la fois un horizon de prédiction long et une résolution temporelle fine. Pour répondre à cette problématique, le modèle fonctionnel est couplé à deux niveaux d'optimisation supérieurs qui permettent de déterminer respectivement l'architecture optimale du système et les plannings de démarrages, d'arrêts et de charge des moyens de production. Cette approche est validée avec la conception et le pilotage d'un réseau urbain multi-énergies dans la commune de Bolbec<br>In order to face the increasing complexity of the developed systems, this thesis proposes a multi-view methodological approach allowing to accompany the stages of the development cycle of complex systems, including multi-energy systems, from their design to their real time control. A level of arbitration between the different missions of the system is also introduced and enables to test several strategies. This level is illustrated in the case of the electric vehicle with arbitrations between autonomy, vehicle speed and passenger comfort. Functional modeling, on which this work focuses, is the cornerstone of the methodology. This describes in a modular way and through the use of just necessary mathematical models and energy links the behavior of the elements of the system and their interactions. In order to take into account the dynamic response of the elements, their constraints and disturbances, some predictive control algorithms ``PFC'' are developed and implemented within the functional elements. These algorithms are also used to introduce an optimization problem to manage the resources allocation process in a multiple source system. These concepts are applied to the control of a wind farm coupled with a storage unit, taking into account congestion constraints on the electric grid. Finally, the adaptation of this methodology to the optimization of multi-energy systems raises new issues, including the coupling between several energy fields, the consideration of discrete manipulable variables and a conflict between the need for both a high prediction horizon and a fine temporal resolution. To address this issue, the functional model is coupled to two higher levels of optimization that allow to determine respectively the optimal system architecture and the source commitment schedule. This approach is validated on the design and the control of a multi-energy urban network in the town of Bolbec
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Zhang, Xiang Qin. "Estimation du couple généré par un muscle sous SEF à la base de l’EMG évoquée pour le suivi de la fatigue et le contrôle du couple en boucle fermée." Thesis, Montpellier 2, 2011. http://www.theses.fr/2011MON20191/document.
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La stimulation électrique fonctionnelle (SEF) a le potentiel de fournir une amélioration active aux blessés médullaires en termes de mobilité, de stabilité et de prévention des effets secondaires.Dans le domaine des système SEF pour les membres inférieurs, le couple articulaire adéquat doit être fournie de façon appropriée pour effectuer le mouvement prévu et maintenir l'équilibre postural. Toutefois, les changements d'état du muscle tels que la fatigue musculaire est une cause majeure qui dégrade ses performances. En outre, la plupart des patients, dont la blessure médullaire est complète, n'ont pas le retour sensorielle qui permet de détecter la fatigue et les capteurs de couples in-vivo ne sont pas disponible à l'heure actuelle. Les systèmes conventionnels de commande SEF sont soit en boucle ouverte ou pas assez robustes aux changements d'état du muscle. L'objectif de cette thèse est le développement de la prédiction du couple articulaire et la commande en boucle fermée afin d'améliorer les performances de la commande SEF en termes de précision, de robustesse et de sécurité pour les patients.Afin de prédire le couple articulaire induit de la SEF, l'électromyographie (EMG) induit est utilisé pour corréler l'activité musculaire électrique et mécanique. Bien que la fatigue musculaire représente une variation dans le temps, une dépendance aux sujets et aux protocoles, la méthode proposée d'identification adaptative, basée sur le filtre de Kalman, est capable de prédire le couple articulaire variant dans le temps de manière systématique. La robustesse de la prédiction du couple articulaire a été évaluée lors d'une tâche de suivi de la fatigue en expérimentation chez des sujets blessés médulaires.Les résultats montrent une bonne performance de suivi des variations d'état des muscles en présence de fatigue et face à d'autres perturbations. Basé sur les performances de précision de la méthode prédictive proposée, une nouvelle stratégie de commande basée sur le retour EMG, «EMG-Feedback Predictive Control» (EFPC), est proposée afin de contrôler de manière adaptative les séquences de stimulation en compensant la variation dans le temps de l'état du muscle. De plus, cette stratégie de commande permet explicitement d'éviter d'appliquer une stimulation excessive aux patients, et de générer les séquences de stimulation appropriées pour obtenir la trajectoire désirée des couples articulaires<br>Functional electrical stimulation (FES) has the potential to provide active improvement to spinal cord injured (SCI) patients in terms of mobility, stability and side-effect prevention. In the domain of lower limb FES system, elicited muscle force must be provided appropriately to perform intended movement and the torque generation by FES should be accurate not to lose the posture balance. However, muscle state changes such as muscle fatigue is a major cause which degrades its performance. In addition, most of the complete SCI patients don't have sensory feedback to detect the fatigue and in-vivo joint torque sensor is not available yet. Conventional FES control systems are either in open-loop or not robust to muscle state changes. This thesis aims at a development of joint torque prediction and feedback control in order to enhance the FES performance in terms of accuracy, robustness, and safety to the patients.In order to predict FES-induced joint torque, evoked-Electromyography (eEMG) has been applied to correlate muscle electrical activity and mechanical activity. Although muscle fatigue represents time-variant, subject-specific and protocol-specific characteristics, the proposed Kalman filter-based adaptive identification was able to predict the time-variant torque systematically. The robustness of the torque prediction has been investigated in a fatigue tracking task in experiment with SCI subjects. The results demonstrated good tracking performance for muscle variations and against some disturbances.Based on accurate predictive performance of the proposed method, a new control strategy, EMG-Feedback Predictive Control (EFPC), was proposed to adaptively control stimulation pattern compensating to time-varying muscle state changes. In addition, this control strategy was able to explicitly avoid overstimulation to the patients, and conveniently generate appropriate stimulation pattern for desired torque trajectory
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Hong, Feng. "Multivariable predictive control development and application in food extrusion processes /." free to MU campus, to others for purchase, 1999. http://wwwlib.umi.com/cr/mo/fullcit?p9946262.
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Norstedt, Erik, and Olof Bräne. "Model Predictive Climate Control for Electric Vehicles." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-446435.
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This thesis explores the possibility of using an optimal control scheme called Model Predictive Control (MPC), to control climatization systems for electric vehicles. Some components of electric vehicles, for example the batteries and power electronics, are sensitive to temperature and for this reason it is important that their temperature is well regulated. Furthermore, like all vehicles, the cab also needs to be heated and cooled. One of the weaknesses of electric vehicles is their range, for this reason it is important that the temperature control is energy efficient. Once the range of electric vehicles is increased the down sides compared to traditional combustion engine vehicles decrease, which could lead to an increase in the usage of electric vehicles. This could in turn lead to a decrease of greenhouse gas emission in the transportation sector. With the help of MPC it is possible for the controller to take more factors into consideration when controlling the system than just temperature and in this thesis the power consumption and noise are also taken into consideration. A simple model where parts of the climate system’s circuits were seen as point masses was developed, with nonlinear heat transfers occurring between them, which in turn were controlled by actuators such as fans, pumps and valves. The model was created using Simulink and MATLAB, and the MPC toolbox was used to develop nonlinear MPC controllers to control the climate system. A standard nonlinear MPC, a nonlinear MPC with custom cost functions and a PI controller where all developed and compared in simulations of a cooling scenario. The controllers were designed to control the temperatures of the battery, power electronics and the cab of an electric vehicle. The results of the thesis indicate that MPC could reduce power consumption for the climate control system, it was however not possible to draw any final conclusions as the PI controller that the MPC controllers were compared to was not well optimized for the system. The MPC controllers could benefit from further work, most importantly by applying a more sophisticated tuning method to the controller weights. What was certain was that it is possible to apply this type of centralized controller to very complex systems and achieve robustness without external logic. Even with the controller keeping track of six different temperatures and controlling 15 actuators, the control loop runs much faster than real time on a modern computer which shows promise with regard to implementing it on an embedded system.
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Tavahodi, Mana. "Mixed model predictive control with energy function design for power system." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16374/1/Mana_Tavahodi_Thesis.pdf.
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For reliable service, a power system must remain stable and capable of withstanding a wide range of disturbances especially for the large interconnected systems. In the last decade and a half and in particular after the famous blackout in N.Y. U.S.A. 1965, considerable research effort has gone in to the stability investigation of power systems. To deal with the requirements of real power systems, various stabilizing control techniques were being developed over the last decade. Conventional control engineering approaches are unable to effectively deal with system complexity, nonlinearities, parameters variations and uncertainties.
This dissertation presents a non-linear control technique which relies on prediction of the large power system behaviour. One example of a large modern power system formed by interconnecting the power systems of various states is the South-Eastern Australian power network made up of the power systems of Queensland, New South Wales, Victoria and South Australia. The Model Predictive Control (MPC) for the total power system has been shown to be successful in addressing many large scale nonlinear control problems. However, for application to the high order problems of power systems and given the fast control response required, total MPC is still expensive and is structured for centralized control.
This thesis develops a MPC algorithm to control the field currents of generators incorporating them in a decentralized overall control scheme. MPC decisions are based on optimizing the control action in accordance with the predictions of an identified power system model so that the desired response is obtained. Energy Function based design provides good control for direct influence items such as SVC (Static Var Compensators), FACTS (Flexible AC Transmission System) or series compensators and can be used to define the desired flux for generator.
The approach in this thesis is to use the design flux for best system control as a reference for MPC. Given even a simple model of the relation between input control signal and the resulting machine flux, the MPC can be used to find the control sequence which will start the correct tracking. The continual recalculation of short time optimal control and then using only the initial control value provides a form of feedback control for the system in the desired tracking task but in a manner which retains the nonlinearity of the model.
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Tavahodi, Mana. "Mixed model predictive control with energy function design for power system." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16374/.
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For reliable service, a power system must remain stable and capable of withstanding a wide range of disturbances especially for the large interconnected systems. In the last decade and a half and in particular after the famous blackout in N.Y. U.S.A. 1965, considerable research effort has gone in to the stability investigation of power systems. To deal with the requirements of real power systems, various stabilizing control techniques were being developed over the last decade. Conventional control engineering approaches are unable to effectively deal with system complexity, nonlinearities, parameters variations and uncertainties. This dissertation presents a non-linear control technique which relies on prediction of the large power system behaviour. One example of a large modern power system formed by interconnecting the power systems of various states is the South-Eastern Australian power network made up of the power systems of Queensland, New South Wales, Victoria and South Australia. The Model Predictive Control (MPC) for the total power system has been shown to be successful in addressing many large scale nonlinear control problems. However, for application to the high order problems of power systems and given the fast control response required, total MPC is still expensive and is structured for centralized control. This thesis develops a MPC algorithm to control the field currents of generators incorporating them in a decentralized overall control scheme. MPC decisions are based on optimizing the control action in accordance with the predictions of an identified power system model so that the desired response is obtained. Energy Function based design provides good control for direct influence items such as SVC (Static Var Compensators), FACTS (Flexible AC Transmission System) or series compensators and can be used to define the desired flux for generator. The approach in this thesis is to use the design flux for best system control as a reference for MPC. Given even a simple model of the relation between input control signal and the resulting machine flux, the MPC can be used to find the control sequence which will start the correct tracking. The continual recalculation of short time optimal control and then using only the initial control value provides a form of feedback control for the system in the desired tracking task but in a manner which retains the nonlinearity of the model.
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Yevseienko, Oleg, Anatoliy Gapon, and Dmytro Salnikov. "Searching for Optimal Control Parameters of Thermal Object Using Pulse-Width Modulation (PWM) Control with Predictive Filter." Thesis, Lviv Polytechnic Publishing House, 2015. http://repository.kpi.kharkov.ua/handle/KhPI-Press/41116.
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The thesis is devote to the temperature control of objects with lumped or distributed parameters. The problems of choosing the right value of regulator’s heater power and prediction period are discussed. The major attention is paid to the process of searching the minimum value of control quantities. It is shown that the approximated second-order plane has an exact accordance with the original data. It is concluded that algorithm of PWM-control with prediction filter provides good quality control.
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Botelho, Viviane Rodrigues. "Auditoria e diagnóstico de modelos para controladores preditivos industriais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/133143.
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A crescente demanda pela melhoria operacional dos processos aliada ao desenvolvimento da tecnologia da informação tornam a utilização de controladores preditivos baseados em modelos (MPC) uma prática comum na indústria. Estes controladores estimam, a partir dos dados de planta e de um modelo do processo, uma sequência de ações de controle que levam as variáveis ao valor desejado de forma otimizada. Dessa forma, dentre os parâmetros de configuração de um MPC, a baixa qualidade do modelo é, indiscutivelmente, a mais importante fonte de degradação de seu desempenho. Este trabalho propõe uma série de metodologias para a avaliação da qualidade do modelo do controlador preditivo, as quais consideram sua velocidade em malha fechada. Tais metodologias são baseadas na filtragem dos erros de simulação a partir função nominal de sensibilidade, e possuem a capacidade de informar o impacto dos problemas de modelagem no desempenho do sistema, além de localizar as variáveis controladas que estão com tais problemas e se os mesmos são provenientes de uma discrepância no modelo ou de um distúrbio não medido. As técnicas ainda possuem a vantagem de serem independentes do setpoint, o que as torna flexível de também serem utilizadas em controladores nos quais as variáveis são controladas por faixas. A abordagem proposta foi testada em dois estudos de caso simulados, sendo eles: a Fracionadora de Óleo Pesado da Shell e a Planta de Quatro tanques Cilíndricos. As técnicas também foram avaliadas em dados de processo da Unidade de Coqueamento Retardado de uma refinaria. Os resultados indicam que as mesmas apresentam resultados coerentes, corroborando seu elevado potencial de aplicação industrial.<br>The growing demand for operational improvement and the development of information technology make the use of model predictive controllers (MPCs) a common practice in industry. This kind of controller uses past plant data and a process model to estimate a sequence of control actions to lead the variables to a desired value following an optimal policy. Thus, the model quality is the most important source of MPC performance degradation. This work proposes a series of methods to investigate the controller model quality taking into account its closed loop performance. The methods are based on filtering the simulation errors using the nominal sensitivity function. They are capable detect the impact of modeling problems in the controller performance, and also to locate the controlled variables that have such problems and if it is caused by a model-plant mismatch or unmeasured disturbance. The techniques have the advantage to be setpoint independent, making them flexible to be also used in MPCs with controlled variables working by range. The proposed approach was tested in two simulated case studies The Shell Heavy Oil Fractionator Process and The Quadruple-tanks Process. The methods are also evaluated in process data of the Delayed Coking Unit of a Brazilian refinery. Results indicate that the method is technically coherent and has high potential of industrial application.
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Raghu, Anand. "Prediction of workpiece location as a function of fixture-induced errors." Thesis, Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/18840.
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Lee, Jong Min. "A Study on Architecture, Algorithms, and Applications of Approximate Dynamic Programming Based Approach to Optimal Control." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5048.
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This thesis develops approximate dynamic programming (ADP) strategies suitable for process control problems aimed at overcoming the limitations of MPC, which are the potentially exorbitant on-line computational requirement and the inability to consider the future interplay between uncertainty and estimation in the optimal control calculation. The suggested approach solves the DP only for the state points visited by closed-loop simulations with judiciously chosen control policies. The approach helps us combat a well-known problem of the traditional DP called 'curse-of-dimensionality,' while it allows the user to derive an improved control policy from the initial ones. The critical issue of the suggested method is a proper choice and design of function approximator. A local averager with a penalty term is proposed to guarantee a stably learned control policy as well as acceptable on-line performance. The thesis also demonstrates versatility of the proposed ADP strategy with difficult process control problems. First, a stochastic adaptive control problem is presented. In this application an ADP-based control policy shows an "active" probing property to reduce uncertainties, leading to a better control performance. The second example is a dual-mode controller, which is a supervisory scheme that actively prevents the progression of abnormal situations under a local controller at their onset. Finally, two ADP strategies for controlling nonlinear processes based on input-output data are suggested. They are model-based and model-free approaches, and have the advantage of conveniently incorporating the knowledge of identification data distribution into the control calculation with performance improvement.
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Hong, Xia. "Non-linear time series modelling and prediction with radial basis function network based algorithms." Thesis, University of Sheffield, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286888.
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Kommaraju, Mallik. "Predictor development for controlling real-time applications over the Internet." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4813.
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Over the past decade there has been a growing demand for interactive multimedia
applications deployed over public IP networks. To achieve acceptable Quality of Ser-
vice (QoS) without significantly modifying the existing infrastructure, the end-to-end
applications need to optimize their behavior and adapt according to network char-
acteristics. Most existing application optimization techniques are based on reactive
strategies, i.e. reacting to occurrences of congestion. We propose the use of predic-
tive control to address the problem in an anticipatory manner. This research deals
with developing models to predict end-to-end single flow characteristics of Wide Area
Networks (WANs).
A novel signal, in the form of single flow packet accumulation, is proposed for
feedback purposes. This thesis presents a variety of effective predictors for the above
signal using Auto-Regressive (AR) models, Radial Basis Functions (RBF) and Sparse
Basis Functions (SBF). The study consists of three sections. We first develop time-
series models to predict the accumulation signal. Since encoder bit-rate is the most
logical and generic control input, a statistical analysis is conducted to analyze the
effect of input bit-rate on end-to-end delay and the accumulation signal. Finally,
models are developed using this bit-rate as an input to predict the resulting accu-
mulation signal. The predictors are evaluated based on Noise-to-Signal Ratio (NSR)
along with their accuracy with increasing accumulation levels. In time-series models, RBF gave the best NSR closely followed by AR models. Analysis based on accu-
racy with increasing accumulation levels showed AR to be better in some cases. The
study on effect of bit-rate revealed that bit-rate may not be a good control input on
all paths. Models such as Auto-Regressive with Exogenous input (ARX) and RBF
were used to develop models to predict the accumulation signal using bit-rate as a
modeling input. ARX and RBF models were found to give comparable accuracy, with
RBF being slightly better.
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Yates, Tony Lomax. "Insulin sensitivity functions predicting using deconvolution in a model of glucose metabolism." Thesis, University of Salford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313872.
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Tastambekov, Kairat. "Aircraft trajectory prediction by local functional regression." Thesis, Toulouse, INSA, 2012. http://www.theses.fr/2012ISAT0052/document.
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Les systèmes de contrôle aérien donneront, dans un avenir assez proche, une plus grande autonomie et liberté d’action aux pilotes (en particulier dans le cadre de la “planification 4D des trajectoires”), ce qui nécessite une prévision de trajectoire de qualité, afin d’une part d’éviter les « conflits » entre avions (avions trop proches, d’où un risque de collision), d’autre part de réguler efficacement les temps d’arrivée aux aéroports.Les trajectoires dépendent de facteurs extérieurs souvent pas, ou mal connus ; en particulier les vents ne sont pas connus avec la précision nécessaire pour une prévision de trajectoire de qualité. De sorte que la prévision de trajectoire ne peut être faite de façon utilisable qu’à court ou moyen terme, disons dans un horizon de moins de 10 minutes ou de l’ordre de 10 à 30 minutes.On appelle “trajectoire 4D” la trajectoire d’un avion, dans l’espace 4D constitué des trois dimensions d’espace, et de la dimension du temps. L’objet de cette thèse est d’établir des méthodes de prévision de trajectoires 4D à court et moyen terme (jusqu’à 10 à 30 minutes). Une telle prévision prend en compte (éventuellement implicitement) des facteurs importants tels que le type de l’appareil, les conditions atmosphériques (vent, température), de façon à pouvoir en déduire les actions précises pour résoudre les conflits potentiels, et/ou arriver à l’instant t voulu à l’aéroport.Dans ce travail, nous présentons une nouvelle approche pour la prédiction des trajectoires d’avion. Cette méthode est basée sur une régression fonctionnelle linéaire, et comprend en particulier un prétraitement des données (lissage, mais surtout synchronisation et cadencement régulier en temps), résolution de la régression par l’utilisation d’une décomposition en ondelettes. On commence par collecter un nombre important de données concernant les vols ayant existé entre deux aéroports ; ces données comportent en particulier les coordonnées, vitesses et projection de l’avion à différents temps. L’étape suivante, que nous appelons localisation, consiste à déterminer un certain nombre de trajectoires “logiquement proches”, c’est à dire, en particulier, concernant le même type d’appareil, et concernant les mêmes aéroports d’origine et de destination. Cet ensemble de trajectoires est ensuite utilisé pour construire un modèle type, qui se rapproche le plus possible de la partie connue de la trajectoire en cours, à prolonger ; ceci est réalisé grâce à une régression fonctionnelle linéaire. Le “modèle type” est alors utilisé comme prédicteur de la trajectoire en cours. Remarquons que cet algorithme n’utilise que des mesures radar, et ne prend pas en compte explicitement des données importantes physiques ou aéronautiques. Cependant les trajectoires ayant servi pour construire le modèle type dépendant elles aussi de ces données, ces dernières sont implicitement prises en compte par cette démarche.Nous avons appliqué cette méthode sur de nombreuses trajectoires entre plusieurs aéroports français, la base de données s’étendant sur plus d’un an. Près de trois millions de vols ont été pris en compte. Les résultats sont présentés en fin du manuscrit ; ils présentent en particulier l’erreur de prédiction, qui est la différence entre la prédiction de la trajectoire et la trajectoire effective (connue puisqu’il s’agit de trajectoires ayant existé, mais bien sûr non utilisée à partir de l’instant où démarre la prévision de trajectoire). Ces résultats montrent que l’erreur de prédiction relative (différence relative entre l’erreur de prédiction et la déviation standard) est de l’ordre de 2% à 16 %. Les résultats obtenus sont meilleurs que ceux obtenus avec la régression linéaire multivariée standard, comme présenté en fin du manuscrit. Rappelons que la méthode est intrinsèque, ne dépend en particulier pas de la structure de l’espace aérien<br>Air Traffic Management (ATM) heavily rely on the ability to predict where an aircraft will be located in a 10-minute time window. So it is clear that a controller’s workload can be reduced by an accurate and automated forecast of aircraft trajectories, since knowing whether conflicts are to be expected helps in prioritizing the actions to be taken.Despite the increasing autonomy in future air traffic management systems, especially 4D trajectory planning, the ability of trajectory prediction is still actual. As known, 4D trajectory planning implies aircraft will be properly located in a certain place at a certain time. However, such an approach is not realistic. Because, in particular, of the wind, Present Flight Management Systems are not able to predict precisely the position of an aircraft in a window larger than, say 15 minutes. For this reason, trajectory prediction problem can be stated as an actual issues at least for the near future. We consider the problem of short to mid-term aircraft trajectory prediction, that is, the estimation of where an aircraft will be located over a 10 to 30 minutes time horizon. Such a problem is central in the decision support tools, especially in conflict detection and resolution algorithms. It also appears when an air traffic controller observes traffic on the radar screen and tries to identify convergent aircraft, which may be in conflict in the near future, in order to apply maneuvers that will separate them. The problem is then to estimate where the aircraft will be located in the time horizon of 10 - 30 minutes. A 4-dimensional (4D) trajectory prediction contains data specifying the predicted horizontal and vertical position of an aircraft. The ability to accurately predict trajectories for different types of aircraft under different flight conditions, that involving external actions (pilot, ATC) and atmospheric influences (wind, temperature), is an important factor in determining the accuracy and effectiveness of ATM.In this work, we present an innovative approach for aircraft trajectory prediction in this work. It is based on local linear functional regression that considers data preprocessing, localizing and solving linear regression using wavelet decomposition. This approach starts from collecting the data set, consisting of a large enough amounts of aircraft trajectories between several airports, in order to make statistical procedures useful. It is necessary to note that ATC radar observations for a given aircraft are a discrete collection of aircraft coordinates, speed, projections, and other factors depending on the radar system. The next step, called localization, is to select a subset of trajectories of the same type of aircraft and connecting the same Origin-Destination as an aircraft trajectory to be predicted. Let us denote an aircraft trajectory to be predicted as a real trajectory. Then, the selected subset is taken as a learning data set to construct a model which is a linear functional regression model. The first part of real aircraft is also taken as a learning set to the model, and the second part is taken to compare it with the predicted part, which is a linear functional regression model. This algorithm takes into account only past radar tracks, and does not make use of any physical or aeronautical parameters.This approach has been successfully applied to aircraft trajectories between several airports on the data set (one year of air traffic over France). The data set consists of more than 2.9*10^6 flights. Several examples at the end of the manuscript show that the relative prediction error that is the difference between prediction error and standard deviation is about 2 to 16 per cents. The proposed algorithm shows better results compares to the standard multiple linear regressions that is shown from the figures at the end of the manuscript. The method is intrinsic and independent from airspace structure
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Kornuta, Jeffrey Alan. "Characterization of lymphatic pump function in response to mechanical loading." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/52208.
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The lymphatic system is crucial for normal physiologic function, performing such basic functions as maintaining tissue fluid balance, trafficking immune cells, draining interstitial proteins, as well as transporting fat from the intestine to the blood. To perform these functions properly, downstream vessels (known as collecting lymphatics) actively pump like the heart to dynamically propel lymph from the interstitial spaces of the body to the blood vasculature. However, despite the fact that lymphatics are so important, there exists very little knowledge regarding the details of this active pumping. Specifically, it is known that external mechanical loading such as fluid shear stress and circumferential stress due to transmural pressure affect pumping response; however, anything other than simple, static relationships remain unknown. Because mechanical environment has been implicated in lymphatic diseases such as lymphedema, understanding these dynamic relationships between lymphatic pumping and mechanical loading during normal function are crucial to grasp before these pathologies can be unraveled. For this reason, this thesis describes several tools developed to study lymphatic function in response to the unique mechanical loads these vessels experience both in vitro and ex vivo. Moreover, this work investigates how shear stress sensitivity is affected by transmural pressure and how the presence of dynamic shear independently affects lymphatic contractile function.
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Capancioni, Alessandro. "Development of a predictive thermal management function for Plug-in Hybrid Electric Vehicles." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15248/.
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The present thesis is focused on the development of a predictive control strategy oriented to battery thermal management for plug-in hybrid electric vehicles (PHEVs). The basic principle of the strategy is to reduce as much as possible battery energy usage related to power request from the respective cooling circuit actuators. At this end, a thermo-hydraulic model of the in-vehicle battery cooling circuit has been developed in AMESim environment. Then, it has been implemented in an already existing Simulink vehicle model, which includes components analytical models and control strategies. The predictive aspect of the novel strategy is related to the evaluation of battery temperature over the electronic horizon on the base of input signals such as vehicle speed and road slope profile. As a consequence of temperature prediction, the developed strategy is able to establish in an energy-efficient way if cooling power is either required or not. Results highlight the advantages of applying the predictive strategy instead of a rule-based one, which is on-board implemented in each vehicle. It is shown that major energetic benefits, related to the extension of the all-electric range and the reduction of fuel consumption, take place at middle environmental temperatures, at which battery cooling power request can seriously make the difference on its drain rate. Therefore, project goal has been reached and the results can be considered an interesting starting point for further development and enhancing of predictive control strategies.
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Ögren, Petter. "Formations and Obstacle Avoidance in Mobile Robot Control." Doctoral thesis, KTH, Mathematics, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3555.
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<p>This thesis consists of four independent papers concerningthe control of mobile robots in the context of obstacleavoidance and formation keeping.</p><p>The first paper describes a new theoreticallyv erifiableapproach to obstacle avoidance. It merges the ideas of twoprevious methods, with complementaryprop erties, byusing acombined control Lyapunov function (CLF) and model predictivecontrol (MPC) framework.</p><p>The second paper investigates the problem of moving a fixedformation of vehicles through a partiallykno wn environmentwith obstacles. Using an input to state (ISS) formulation theconcept of configuration space obstacles is generalized toleader follower formations. This generalization then makes itpossible to convert the problem into a standard single vehicleobstacle avoidance problem, such as the one considered in thefirst paper. The properties of goal convergence and safetyth uscarries over to the formation obstacle avoidance case.</p><p>In the third paper, coordination along trajectories of anonhomogenuos set of vehicles is considered. Byusing a controlLyapunov function approach, properties such as boundedformation error and finite completion time is shown.</p><p>Finally, the fourth paper applies a generalized version ofthe control in the third paper to translate,rotate and expanda formation. It is furthermore shown how a partial decouplingof formation keeping and formation mission can be achieved. Theapproach is then applied to a scenario of underwater vehiclesclimbing gradients in search for specific thermal/biologicalregions of interest. The sensor data fusion problem fordifferent formation configurations is investigated and anoptimal formation geometryis proposed.</p><p><b>Keywords:</b>Mobile Robots, Robot Control, ObstacleAvoidance, Multirobot System, Formation Control, NavigationFunction, Lyapunov Function, Model Predictive Control, RecedingHorizon Control, Gradient Climbing, Gradient Estimation.</p>
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Canè, Stella. "Development of a Predictive Control Function for a Plug-in Hybrid Electric Vehicle with Electrically-heated Catalyst." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24073/.
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This master thesis work is focused on the development of a predictive EHC control function for a diesel plug-in hybrid electric vehicle equipped with a EURO 7 compliant exhaust aftertreatment system (EATS), with the purpose of showing the advantages provided by the implementation of a predictive control strategy with respect to a rule-based one. A preliminary step will be the definition of an accurate powertrain and EATS physical model, starting from already existing and validated applications. Then, a rule-based control strategy managing the torque split between the electric motor (EM) and the internal combustion engine (ICE) will be developed and calibrated, with the main target of limiting tailpipe NOx emission by taking into account EM and ICE operating conditions together with EATS conversion efficiency. The information available from vehicle connectivity will be used to reconstruct the future driving scenario, also referred to as electronic horizon (eHorizon), and in particular to predict ICE first start. Based on this knowledge, an EATS pre-heating phase can be planned to avoid low pollutant conversion efficiencies, thus preventing high NOx emission due to engine cold start. Consequently, the final NOx emission over the complete driving cycle will be strongly reduced, allowing to comply with the limits potentially set by the incoming EURO 7 regulation. Moreover, given the same NOx emission target, the gain achieved thanks to the implementation of an EHC predictive control function will allow to consider a simplified EATS layout, thus reducing the related manufacturing cost.
The promising results achieved in terms of NOx emission reduction show the effectiveness of the application of a predictive control strategy focused on EATS thermal management and highlight the potential of a complete integration and parallel development of involved vehicle physical systems, control software and connectivity data management.
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Belghali, Maroua. "New methodological approach for the evaluation of executive function, gait control and cognitive reserve : perspectives for earlier prediction of Alzheimer's and Parkinson's diseases." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMC402.
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La maladie d’Alzheimer (MA) et la maladie de Parkinson (MP), sont considérées aujourd’hui comme un problème majeur de santé publique du fait qu’elles sont diagnostiquées trop tardivement et demeurent sans traitement curatif. D’importants efforts doivent donc être mis en œuvre pour identifier des marqueurs précliniques sensibles et spécifiques au risque de développer une maladie neurodégénérative. Dans cette optique, plusieurs auteurs ont récemment montré que les fonctions exécutives et le control locomoteur dans une situation de double tâche, sont altérés aux stades précliniques de la MA et la MP. En routine clinique les médecins sont des fois confrontées à ces individus ayant des troubles exécutivo-locomoteurs mais qui ne sont pas immédiatement repérés en raison de leurs capacités de réserves particulièrement élevées. Pris ensemble, les travaux de cette thèse s’articulent autour d’un large spectre des notions liées au vieillissement normal et pathologique qui sont les fonctions exécutives, le contrôle locomoteur et la réserve cognitive. L’originalité de cette thèse réside dans le développement d’un « nouveau test neuropsychologique : Le Stroop Switching Card Test » évaluant l’efficience exécutive globale avec des mesures spécifiques à chaque composante et deux nouvelles mesures de la réserve cognitive dont une qualitative (i.e., un nouveau questionnaire) et l’autre quantitative (seuil du déclin exécutif associé à une basse réserve cognitive). En parallèle nous avons développé trois nouveaux paradigmes de doubles tâches fondés sur le profil physiopathologique de la MA et la MP. Les résultats révèlent que la batterie de tests que nous proposons présente un intérêt potentiel pour détecter précocement un déclin exécutif chez les sujets âgés, mais aussi pour distinguer le vieillissement normal du vieillissement accéléré. En conclusion, les résultats préliminaires de cette thèse confirment la validité de nouveaux tests dans l’évaluation des fonctions exécutive, de la réserve cognitive et du contrôle locomoteur. Des études longitudinales sont nécessaires pour confirmer que ces outils pourraient avoir une valeur ajoutée dans le diagnostic précoce et différencié des MA et MP<br>To date, Alzheimer’s disease (AD) and Parkinson’s disease (PD) are diagnosed in the advanced stage of degenerative brain processes, when clinical symptoms occur. In the absence of curative therapy, current research is focused on prevention by identifying subtle signs of early stage neurodegeneration. In the light of these clinical perspectives, recent research in behavioral neurosciences has already found that executive functions (i.e., notably inhibition and switching) and gait control as assessed by standard neuropsychological tests (e.g., Stroop Test and Trail Making Test) and dual-task walking paradigms, respectively, are already altered at both the preclinical and prodromal phases of AD and PD. We would argue that it is imperative to take into account factors modulating the capacity to cope with age-related brain changes, among which the most important is the cognitive reserve. Together, the main goals of this thesis are to develop: (i) a new neuropsychological test, assessing executive functions, separately and together, (ii) new measures of CR; and (iii) new dual-task walking paradigms based on the neuropathological profiles of AD and PD, by manipulating both the nature of executive processes and cognitive load. These tools were validated in healthy young adults and older adults with a high sensitivity. Specifically, we have found that these tools allow detecting early executive decline. Furthermore, they allow to differentiate normal aging from accelerated aging. In conclusion, the preliminary results of this thesis confirm the validity of the new tests in the evaluation of executive function, cognitive reserve and gait control. Longitudinal studies are needed to confirm that these tools could have an added value in the early and differential diagnosis of AD and PD
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Machado, Jeremias Barbosa. "Modelagem e controle preditivo utilizando multimodelos." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259984.
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Orientadores: Wagner Caradori do Amaral, Ricardo Jose Grabrielli Barreto Campello<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-09T14:19:44Z (GMT). No. of bitstreams: 1
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Previous issue date: 2007<br>Resumo: o interesse na utilização de algoritmos de controle sofisticados cresce no meio industrial devido à necessidade de melhor qualidade dos produtos produzidos. Uma abordagem que vem ganhando destaque é a utilização de sistemas de controle não-linear que modelam os sistemas por meio de multimodelos lineares. Neste contexto, este trabalho apresenta a modelagem e controle de sistemas não-lineares através de controladores preditivos não-lineares que utilizam multimodelos lineares. Os controladores preditivos baseados em modelos (MBPC - Model Based Predictive Controllers) são controladores cuja principal característica é a utilização de um modelo na determinação de um conjunto de previsões de saída, e a lei de controle é calculada em função destas previsões minimizando-se uma função de custo. O desempenho deste controlador depende da qualidade do modelo utilizado para predição dos sinais de saída. A proposta do trabalho é modelar as não-linearidades do processo sob controle através de modelos fuzzy Takagi-Sugeno - TS com funções de base ortonormal - FBO nos conseqüentes das regras. As FBO's apresentam diversas características conceituais e estruturais de interesse na elaboração dos modelos utilizados nos controladores preditivos, como a ausência de realimentação de saída, o que evita a propagação de erro, além de outras que serão discutidas ao longo deste trabalho. Os parâmetros de um modelo fuzzy TS a serem determinados são os antecedentes das regras, com suas funções de pertinência, e as funções nos conseqüentes das regras, que neste trabalho dar-se-ão de forma automática, sendo os antecedentes das regras obtidos através de agrupamento fuzzy (fuzzy clustering) das amostras de entrada e saída. Para esta tarefa será utilizado o algoritmo de GustafsonKessel. A fim de determinar o número de grupos que irão compor o modelo e, por conseqüência, defil)ir o número de regras e modelos locais, utilizar-se-ão critérios que avaliam a qualidade dos agrupamentos juzzy, como Fuzzy Silhouette, Fuzzy Hipervolume, Average Partition Density e Average Within-Cluster Distance, sendo proposta a combinação dos resultados obtidos em cada um dos critérios. O controle é feito de forma que, para cada modelo local, presente no modelo fuzzy TS-FBO, tem-se um controlador atuando sobre este. As ações de controle locais são combinadas conforme a ativação de cada regra do respectivo modelo local, e a ação de controle global resultante dessa combinação é aplicada ao processo a ser controlado. A abordagem proposta apresenta vantagens estruturais na modelagem e controle de processos nãolineares, quando comparado a outras metodologias de modelagem (como modelos polinomiais NARMAX) e controle, uma vez que esta abordagem é composta de uma estrutura simples com modelos locais lineares (ou afins) formados por FBO's. Para ilustrar o que foi desenvolvido, são apresentadas, no final destes trabalho, implementações na modelagem e controle de processos não-lineares<br>Abstract: The use of advanced control strategies has been increased in the last years due to the needs of more accurate quality on products. An approach that seems attractive on control and modeling of the nonlinear processes is the use of multiple linear models. In this context, this work presents an altemative approach for modeling and controlling nonlinear processes through nonlinear predictive control (NMBPC) using multi-models. The main characteristic of the Model Based Predictive Controllers is the use of a model for the determination ofthe output predictions. The controllaw is derived based on these output predictions, minimizing a specified cost function. Its performance is directly related to the quality of the model predictor. Therefore, in this work, the process is modeling through Takagi-Sugeno- TS fuzzy models with orthonormal base functions - OBF - on the mIes consequents. OBF' s models present several conceptual and structural characteristics of interest on the elaboration of models predictors, such as, absence of output recursion and feedback of prediction errors, often leading to superior performances over long-range horizon predictions and natural decoupling between multiple outputs; there is no need for previous knowledge about the relevant past terms of the system signals; the representation of a stable system is assuredly stable; tolerance to unmodeled dynamics; ability to deal with time delays. The antecedents ofthe TS fuzzy models are obtained through fuzzy c1ustering ofthe input and output measures. The algorithm of Gustafson-Kessel is used to perform this task. In order to determine the number ofthe local models, clustering validity criteria such as Fuzzy Silhouette, Fuzzy Hipervolume, Average Partition Density e Average Within-Cluster Distance are used. A predictive controller is derived for local model and the global controllaw is obtained by combining each local control law, using the degree of activation of every mIe of the respective local model. The proposed approach presents structural advantages in the modeling and controlling nonlinear process, when compared to other modeling (like polynomial models-NARMAX) and controlling strategies, as this approach is constituted of a simple structure with linear local models using OBF' s. The performance of the proposed strategies is illustrated using some simulated examples<br>Mestrado<br>Automação<br>Mestre em Engenharia Elétrica
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Lindmaa, Alexander. "Theoretical prediction of properties of atomistic systems : Density functional theory and machine learning." Doctoral thesis, Linköpings universitet, Teoretisk Fysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139767.
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The prediction of ground state properties of atomistic systems is of vital importance in technological advances as well as in the physical sciences. Fundamentally, these predictions are based on a quantum-mechanical description of many-electron systems. One of the hitherto most prominent theories for the treatment of such systems is density functional theory (DFT). The main reason for its success is due to its balance of acceptable accuracy with computational efficiency. By now, DFT is applied routinely to compute the properties of atomic, molecular, and solid state systems. The general approach to solve the DFT equations is to use a density-functional approximation (DFA). In Kohn-Sham (KS) DFT, DFAs are applied to the unknown exchangecorrelation (xc) energy. In orbital-free DFT on the other hand, where the total energy is minimized directly with respect to the electron density, a DFA applied to the noninteracting kinetic energy is also required. Unfortunately, central DFAs in DFT fail to qualitatively capture many important aspects of electronic systems. Two prime examples are the description of localized electrons, and the description of systems where electronic edges are present. In this thesis, I use a model system approach to construct a DFA for the electron localization function (ELF). The very same approach is also taken to study the non-interacting kinetic energy density (KED) in the slowly varying limit of inhomogeneous electron densities, where the effect of electronic edges are effectively included. Apart from the work on model systems, extensions of an exchange energy functional with an improved KS orbital description are presented: a scheme for improving its description of energetics of solids, and a comparison of its description of an essential exact exchange feature known as the derivative discontinuity with numerical data for exact exchange. An emerging alternative route towards the prediction of the properties of atomistic systems is machine learning (ML). I present a number of ML methods for the prediction of solid formation energies, with an accuracy that is on par with KS DFT calculations, and with orders-of-magnitude lower computational cost.<br>Att kunna förutsäga egenskaper hos atomistiska system utgör en viktigdel av vår teknologiska utveckling, samt spelar en betydande roll i defysikaliska vetenskaperna. Sådana förutsägelser bygger på en kvantmekaniskbeskrivning av mångelektronsystem. En av de mest framståendeteorierna för att behandla den här typen av system är täthetsfunktionalteorin(DFT). Den främsta orsaken till dess framgång är attden lyckas kombinera skaplig noggrannhet med en bra beräkningseffektivitet.DFT används numera rutinmässigt för att beräkna storheterhos atomer, molekyler, och fasta kroppar. Generellt sett löses ekvationerna inom DFT genom att man inför entäthetsfunktionalapproximation (DFA). I Kohn-Sham (KS) DFT, användsDFAer för att approximera utbytes-korrelationsenergin. Inom orbitalfriDFT, där målet är att direkt minimera den totala energin med avseendepå elektrontätheten, så approximerar man också den icke-interageranderörelseenergin hos elektronerna. Dessvärre så fallerar många centralaDFAer att kvalitativt beskriva många viktiga aspekter hos elektronsystem.Två viktiga exempel är beskrivningen av lokaliserade elektroner,samt beskrivningen av system där det förekommer elektronytor. I denna avhandling använder jag modellsystem för att konstruera enDFAför elektronlokaliseringsfunktionen (ELF). Samma tillvägagångssättappliceras sedan för att studera den kinetiska energitätheten i gränsen avlångsamt varierande elektrontätheter, där effekten av elektronytor effektivtinkluderas. Förutom arbetet som berör modellsystem, så presenterasen utökad variant av en utbytes-energifunktional med en förbättrad KSorbitalbeskrivning: ett schema för att förbättra dess energiegenskaperför solida material, samt en jämförelse av dess beskrivning av en viktigegenskap hos den exakta utbytesenergin, vilket utgörs av diskontinuiteteri dess derivata. Ett mera nyligen uppkommet samt alternativt sätt att kunna förutsägaegenskaper hos atomistiska system utgörs av maskinlärning (ML).Jag presenterar ett antal ML-modeller för att kunna förutsäga formeringsenergierhos fasta material med en noggrannhet som är i linje medresultat som uppnås av beräkningar med hjälp av KS DFT, och med enberäkningseffektivitet som är flera storleksordningar snabbare.
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Chebassier, Joël. "Méthodologies pour la conception d'un système de commande par calculateur." Grenoble INPG, 1999. http://www.theses.fr/1999INPG0006.
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La motivation principale de ce travail est de reunir les connaissances offertes par l'automatique en vue de developper une approche ingenieur pour la synthese d'un systeme de commande. Cette approche a ete mise en oeuvre dans l'environnement du logiciel simart pour permettre d'apprehender relativement facilement les techniques d'identification et de commande des systemes. La formulation des problemes d'identification et de commande a ete faite avec l'operateur delta pour permettre de traiter d'une maniere unifiee les systemes continus et les systemes echantillones. Le developpement des etapes suivantes s'est avere essentiel pour la methodologie de synthese des systemes de commande que nous avons proposee : _ la reformulation avec l'operateur delta des principales methodes predictives de l'identification des systemes et de la commande predictive. _ le developpement d'une procedure de specification des parametres de synthese pour la commande predictive. _ la proposition d'une nouvelle methode d'identification en boucle fermee basee sur la restauration du comportement d'entree-sortie du systeme de commande. _ l'introduction d'une procedure de validation des performances realisees a partir d'une analyse spectrale du comportement d'entree-sortie du systeme de commande. De nombreuses applications en temps reels ont ete faites pour valider la methodologie proposee et mettre en evidence que le compromis performances/simplicite recherche est tout a fait realisable.
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Leising, Sophie. "Nonlinear controller synthesis for complex chemical and biochemical reaction systems." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050205-152657/.
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Thesis (M.S.) -- Worcester Polytechnic Institute.<br>Keywords: model predictive control; discrete-time model; continuous-time model; nonlinear systems; Lyapunov design. Includes bibliographical references (p. 99-102).
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Anaya, Berenice. "Self-Regulation in Preschoolers: Validity of Hot and Cool Tasks as Predictive Measures of Academic and Socio-Emotional Aspects of School Readiness." TopSCHOLAR®, 2016. http://digitalcommons.wku.edu/theses/1644.
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Extensive research on the development of self-regulation has demonstrated that better executive functioning and effortful control during the preschool years are associated with greater kindergarten and early school achievement. Recent findings suggest that self-regulation tasks differ in their assessment of “hot” and “cool” regulation, how these processes map onto effortful control and executive functioning, and may predict school readiness. However, only a few studies have examined the validity of hot and cool regulation tasks (Allan & Lonigan, 2014; Di Norcia, Pecora, Bombi, Baumgartner, & Laghi, 2015; Willoughby, Kupersmidt, Voegler-Lee, & Bryant, 2011), and how they predict socio-emotional competence (Di Norcia et al., 2015) and academic performance (Kim, Nordling, Yoon, Boldt, & Kochanska, 2013). The current study examined the validity of hot and cool tasks as measures of self-regulation and predictive measures of school readiness within a low-income sample. The sample consisted of 64 preschoolers between the ages of three (n= 38) and four (n= 26) who were enrolled in a blended Head Start program. The Preschooler Self-Regulation Assessment, Woodcock Johnson subtests (Letter Word, Applied Problem, and Picture Vocabulary), and teacher ratings of social competence (Social Competence and Behavioral Evaluation) and emotional competence (Emotion Regulation Checklist) were collected in the fall and spring of the school year. Results indicated that performance on the Cool and Hot tasks
was moderate to highly correlated with academic performance and teacher ratings of socio-emotional competence respectively. Developmental differences in selfregulation performance suggested that cool regulation begins to develop later in the preschool period and may depend on earlier development of hot regulatory processes. There were also gains in academic achievement and socio-emotional competence from fall to spring. Regression analyses indicated that Hot and Cool tasks did not predict socio-emotional competence and academic achievement as distinctively as expected. Hot and cool regulation seemed to predict socio-emotional competence and academic achievement in parallel, with the exception of math performance, which was strongly predicted by Cool task performance above and beyond Hot tasks. Results suggest that hot and cool regulation overlap in predicting school readiness.
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Younkin, Timothy R. "Piecewise prediction of nuclide densities with control blade use as a function of burnup in BWR used nuclear fuel." Thesis, Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53118.
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In order to improve the efficiency of dry used nuclear fuel (UNF) storage, reduced reactivity methods are being developed for various reactor types and operating conditions. Sub-criticality must be maintained in the storage configuration and conservative computer simulations are used as the primary basis for loading the storage casks. Methodologies are now being developed to reduce the amount of modeling and computation in order to make conservative assessments of how densely fuel can be packed. The SCALE/TRITON (Standardized Computer Analyses for Licensing Evaluation / Transport Rigor Implemented with Time-dependent Operation for Neutronic Depletion) code system has been used to simulate boiling water reactor (BWR) operating conditions in order to investigate nuclide densities in UNF and how the use of control rod blades affect nuclide densities found in UNF. Rodded and unrodded operating cases for a fuel assembly have been used as bounding cases and are used as reference solutions in a piecewise data approximation methodology (PDA method). A variety of control blade insertion patterns have been used with the PDA method and simulated in TRITON in order to observe trends in nuclide densities with varying control blade use. The PDA method is compared with TRITON simulated data in order to evaluate the validity and accuracy of the PDA method. The PDA method gives very accurate results for fissile nuclides but is insufficient in treating densities as a function of burnup for fission products and fertile nuclides. Predicting nuclide densities from temporally balanced control blade insertion and withdrawal patterns is also a strength of the PDA method. The PDA method, however, is not capable of properly accounting for neutron spectral shifts and the behavior in nuclide densities brought about by the spectral shift or nuclide density saturation. Observing the causes for the shortcomings in the PDA method, a more robust methodology can be developed.
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Caun, Rodrigo da Ponte. "Controle preditivo para sistemas lineares discretos variantes no tempo usando funções de Lyapunov dependentes de caminho." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261576.
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Orientadores: Pedro Luis Dias Peres, Ricardo Coração de Leão Fontoura de Oliveira<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-12T15:25:55Z (GMT). No. of bitstreams: 1
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Previous issue date: 2008<br>Resumo: A principal contribuição dessa dissertação é propor um método de síntese de controle preditivo por realimentação de estados para sistemas lineares discretos com parâmetros variantes no tempo e pertencentes a um politopo. As condições de síntese são formuladas usando-se funções de Lyapunov dependentes de caminho, isto é, a matriz de Lyapunov depende de maneira multi-afim dos parâmetros em seus instantes sucessivos de tempo até um instante máximo (tamanho do caminho). Essa classe de função generaliza as funções quadráticas e dependentes de maneira afim nos parâmetros. Os testes numéricos s¿ao formulados em termos de problemas de otimização baseados em desigualdades matriciais lineares, parametrizados em função do tamanho do caminho da matriz de Lyapunov, arbitrado a priori. À medida que o tamanho do caminho cresce, índices de desempenho menos conservadores são obtidos ao preço de um maior esforço computacional. Exemplos numéricos são apresentados ilustrando a eficiência do método proposto em termos do índice de desempenho e do esforço computacional demandado quando comparados com outros métodos existentes na literatura.<br>Abstract: The main contribution of this thesis is to propose a state-feedback model predictive control design method for discrete-time systems with time-varying parameters belonging to a polytope. The synthesis conditions are formulated using path-dependent Lyapunov functions, i.e. the Lyapunov matrix depends multi-affinely on the parameters at successive instants of time until a maximum instant (path size). This class of function generalizes quadratic and affinely parameter dependent functions. The numerical tests are provided in terms of optimization problems based on linear matrix inequalities, parametrized as a function of the path size of the Lyapunov matrix, given a priori. As the path size increases, less conservative performance indices are obtained at the price of a higher computational effort. Numerical examples are presented, illustrating the efficiency of the approach in terms of the performance index and the computational burden demanded when compared to other existing methods in the literature.<br>Mestrado<br>Automação<br>Mestre em Engenharia Elétrica
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Fomunung, Ignatius Wobyeba. "Predicting emissions rates for the Atlanta on-road light-duty vehicular fleet as a function of operating modes, control technologies, and engine charateristics." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/20834.
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Ngo, Van Quang Binh. "Algorithmes de conception de lois de commande prédictives pour les systèmes de production d’énergie." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLC031/document.
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Cette thèse vise à élaborer de nouvelles stratégies de commande basées sur la commande prédictive pour le système de génération d’énergie éolienne. La topologie des systèmes de production éolienne basées sur le Générateur Asynchrone à Double Alimentation (GADA) qui convient à des plateformes de génération dans la gamme de puissance de 1.5 à 6 MW est abordée. Du point de vue technologique, le convertisseur à trois niveaux et clampé par le neutre (3L-NPC) est considéré comme une bonne solution pour une puissance élevée en raison de ses avantages: capacité à réduire la distorsion harmonique de la tension de sortie et du courant, et augmentation de la capacité du convertisseur grâce à une tension réduite appliquée à chaque semi-conducteur de puissance. Une description détaillée de la commande prédictive à ensemble de commande fini (FCS-MPC) avec un horizon de prédiction de deux pas est présentée pour deux boucles de régulation: celle liée au convertisseur connecté au réseau et celle du convertisseur connecté au GADA. Le principe de la commande repose sur l’utilisation d’un modèle de prédiction permettant de prédire le comportement du système pour chaque état de commutation du convertisseur. La minimisation d’une fonction de coût appropriée prédéfinie permet d’obtenir la commutation optimale à appliquer au convertisseur. La thèse étudie premièrement les problèmes liées à la compensation du temps de calcul de la commande et au choix et aux pondérations de la fonction de coût. Ensuite, le problème de stabilité de la commande FCS-MPC est abordé en considérant une fonction de Lyapunov dans la minimisation de la fonction de coût. Finalement, une étude sur la compensation des effets des temps morts du convertisseur est présentée<br>This thesis aims to elaborate new control strategies based on Model Predictive control for wind energy generation system. We addressed the topology of doubly fed induction generator (DFIG) based wind generation systems which is suitable for generation platform power in the range in 1.5-6 MW. Furthermore, from the technological point of view, the three-level neutral-point clamped (3L-NPC) inverter configuration is considered a good solution for high power due to its advantages: capability to reduce the harmonic distortion of the output voltage and current, and increase the capacity of the converter thanks to a decreased voltage applied to each power semiconductor.In this thesis, we presented a detailed description of finite control set model predictive control (FCS-MPC) with two step horizon for two control schemes: grid and DFIG connected 3L-NPC inverter. The principle of the proposed control scheme is to use system model to predict the behaviour of the system for every switching states of the inverter. Then, the optimal switching state that minimizes an appropriate predefined cost function is selected and applied directly to the inverter.The study of issues such as delay compensation, computational burden and selection of weighting factor are also addressed in this thesis. In addition, the stability problem of FCS-MPC is solved by considering the control Lyapunov function in the design procedure. The latter study is focused on the compensation of dead-time effect of power converter
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Kröber, Wenzel [Verfasser], Helge [Akademischer Betreuer] Bruelheide, Stan [Akademischer Betreuer] Harpole, and Karsten [Akademischer Betreuer] Wesche. "Stomatal control, xylem hydraulics and leaf morphology in the 40 BEF-China tree species : trait interrelationships, functional diversity and tree growth prediction ; [kumulative Dissertation] / Wenzel Kröber. Betreuer: Helge Bruelheide ; Stan Harpole ; Karsten Wesche." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2015. http://d-nb.info/1069532479/34.
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Kröber, Wenzel Verfasser], Helge [Akademischer Betreuer] Bruelheide, Stan [Akademischer Betreuer] Harpole, and Karsten [Akademischer Betreuer] [Wesche. "Stomatal control, xylem hydraulics and leaf morphology in the 40 BEF-China tree species : trait interrelationships, functional diversity and tree growth prediction ; [kumulative Dissertation] / Wenzel Kröber. Betreuer: Helge Bruelheide ; Stan Harpole ; Karsten Wesche." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2015. http://nbn-resolving.de/urn:nbn:de:gbv:3:4-14136.
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Handford, Matthew Lawrence. "Simulating human-prosthesis interaction and informing robotic prosthesis design using metabolic optimization." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1539707296618987.
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Cardoso, Alisson Assis. "Alocação adaptativa de banda e controle de fluxos de tráfego de redes utilizando sistemas Fuzzy e modelagem multifractal." Universidade Federal de Goiás, 2014. http://repositorio.bc.ufg.br/tede/handle/tede/3164.
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Previous issue date: 2014-06-26<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>Inthispaperweproposeafuzzymodel,calledFuzzyLMScomAutocorrela¸c˜aoMultifractal,
whose weights are updated according to information from multifractal traffic modeling.
These weights are calculated by incorporating an analytical expression for the autocorrelation function of a multifractal model in the training algorithm of the fuzzy model that is based on the Wiener-Hopf filter. We evaluate the prediction performance of the proposed network traffic prediction algorithm with respect to other predictors. Further, we propose a bandwidth allocation scheme for network traffic based on the fuzzy prediction algorithm. Comparisons with other bandwidth allocation schemes in terms of byte loss rate, link utilization, buffer occupancy and average queue size verifies the efficiency of the proposed scheme. Also, We propose an other adaptive fuzzy algorithm, called Fuzzy-LMS-OBF com alfa adaptivo , for traffic flow control described by theβMWM model. The proposed
algorithm uses Orthonormal Basis Functions (OBF) and its training based on the LMS
algorithm. We also present an expression for the optimal traffic source rate derived from
Fuzzy LMS. Then, we evaluate the performance of the Fuzzy-LMS-OBF com alfa adaptivo
algorithm with respect to other methods. Through simulations, we show that the proposed
control scheme is benefited from the superior performance of the proposed fuzzy algorithm.
Comparisons with other methods in terms of mean and variance of the queue size in the
buffer, Utilization rate of the link, Loss rate and Throughput are presented.<br>Neste trabalho propomos um modelo fuzzy, nomeado Fuzzy LMS com Autocorrela¸c˜ao Multifractal, cujos pesos s˜ao calculados atrav´es de informa¸c˜oes provindas da an´alise multifractal de s´eries temporais. Esses pesos s˜ao encontrados incorporando uma express˜ao anal´ıtica para a fun¸c˜ao de autocorrela¸c˜ao de um modelo multifractal no algoritmo de treinamento do modelo fuzzy que tem como base o filtro de Wiener-Hopf. Avaliamos ent˜ao o desempenho de predi¸c˜ao de tr´afego de redes do modelo fuzzy proposto adaptativo com
rela¸c˜ao a outros preditores. Em seguida, propomos um esquema de aloca¸c˜ao de banda para tr´afego de redes baseado no algoritmo Fuzzy LMS com Autocorrela¸c˜ao Multifractal. Compara¸c˜oes com outros esquemas de aloca¸c˜ao de banda em termos de taxa de perda de bytes, utiliza¸c˜ao do enlace, ocupa¸c˜ao do buffer e tamanho m´edio da fila comprovam a eficiˆencia do algoritmo no esquema utilizado. Al´em disso, propomos um outro algoritmo fuzzy adaptativo para controle de fluxos de tr´afego que podem ser descritos pelo modelo multifractalβMWM, que chamamos de Fuzzy-LMS-OBF com alfa adaptivo, o qual utiliza
Fun¸c˜oes de Bases Ortonormal (FBO) e tem como base de treinamento, o algoritmo LMS. Propomos tamb´em uma equa¸c˜ao para c´alculo da taxa ´otima de controle derivada do modelo Fuzzy LMS. Em seguida, avaliamos o desempenho do algoritmo de controle adaptativo proposto com rela¸c˜ao a outros m´etodos. Atrav´es de simula¸c˜oes, mostramos que os esquemas de controle e aloca¸c˜ao de taxa se favorecem do desempenho dos algoritmos fuzzy adaptativos propostos. Compara¸c˜oes com outros m´etodos em termos de tamanho m´edio e variˆancia da fila no buffer, Taxa de Utiliza¸c˜ao do enlace e Vaz˜ao s˜ao apresentadas.
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Graf, Miroslav. "Moderní metody řízení střídavých elektrických pohonů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219421.
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This thesis describes the theory of model predictive control and application of the theory to synchronous drives. It shows explicit and on-line solutions and compares the results with classical vector control structure.
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Pouilly-Cathelain, Maxime. "Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG019.
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Cette thèse porte sur la commande des systèmes non linéaires soumis à des contraintes non différentiables ou non convexes. L'objectif est de pouvoir réaliser une commande permettant de considérer tout type de contraintes évaluables en temps réel.Pour répondre à cet objectif, la commande prédictive a été utilisée en ajoutant des fonctions barrières à la fonction de coût. Un algorithme d'optimisation sans gradient a permis de résoudre ce problème d'optimisation. De plus, une formulation permettant de garantir la stabilité et la robustesse vis-à-vis de perturbations a été proposée dans le cadre des systèmes linéaires. La démonstration de la stabilité repose sur les ensembles invariants et la théorie de Lyapunov.Dans le cas des systèmes non linéaires, les réseaux de neurones dynamiques ont été utilisés comme modèle de prédiction pour la commande prédictive. L'apprentissage de ces réseaux ainsi que les observateurs non linéaires nécessaires à leur utilisation ont été étudiés. Enfin, notre étude s'est portée sur l'amélioration de la prédiction par réseaux de neurones en présence de perturbations.La méthode de synthèse de correcteurs présentée dans ces travaux a été appliquée à l’évitement d’obstacles par un véhicule autonome<br>This PhD thesis deals with the control of nonlinear systems subject to nondifferentiable or nonconvex constraints. The objective is to design a control law considering any type of constraints that can be online evaluated.To achieve this goal, model predictive control has been used in addition to barrier functions included in the cost function. A gradient-free optimization algorithm has been used to solve this optimization problem. Besides, a cost function formulation has been proposed to ensure stability and robustness against disturbances for linear systems. The proof of stability is based on invariant sets and the Lyapunov theory.In the case of nonlinear systems, dynamic neural networks have been used as a predictor for model predictive control. Machine learning algorithms and the nonlinear observers required for the use of neural networks have been studied. Finally, our study has focused on improving neural network prediction in the presence of disturbances.The synthesis method presented in this work has been applied to obstacle avoidance by an autonomous vehicle
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Manrique, Espindola Dolly Tatiana. "Commande optimale d’une voiture électrique à faible consommation sous contraintes temps réel." Thesis, Université de Lorraine, 2014. http://www.theses.fr/2014LORR0198/document.
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Le problème de l'efficacité énergétique dans le domaine des transports a comme principal défi savoir comment utiliser la source d'énergie pour que l'efficacité énergétique puisse être maximisée, c'est-à-dire comment le véhicule doit être conduit de telle sorte que la quantité minimale d’énergie est utilisée. Ce problème est le principal problème considéré dans cette thèse. Le véhicule est un prototype impliqué dans la course européenne Shell Eco-Marathon. La dynamique du véhicule est d'abord obtenu par l'identification expérimentale des paramètres. Une stratégie en boucle ouverte de conduite optimale en termes de consommation électrique est calculée. Plusieurs approches ont été étudiées pour le suivi de la référence optimale (stratégie de conduite optimale). Ces approches doivent prendre en compte les ressources limitées en taille mémoire et capacité de calcul. Une commande prédictive (MPC) basée sur la dynamique linéarisée est tout d'abord synthétisée. Le problème de poursuite nécessite une MPC avec contraintes variant dans le temps. La stabilité et la convergence de la commande prédictive sont prouvées à l'aide du formalisme des ensembles invariants. En troisième partie, à partie du modèle LPV, une adaptation de techniques standards basées sur des fonctions de Lyapunov quadratiques et à paramètres variants avec calculs hors-ligne est proposée. Elle est implémentée sur un banc de test. Enfin, une technique adaptative robuste avec identification en ligne de la dynamique est proposée et implémentée dans le véhicule. Cette technique a été testée et validée en course. Les résultats expérimentaux obtenus montrent de bonnes performances de la stratégie de conduite<br>In the field of transportation, the research on energy efficiency has been carried out for few decades by the automotive industry, where one of the main objectives is to reduce the energetic consumption. This particular problem can be rephrased as how the vehicle must be driven so that the minimum quantity of energy is used. This is the optimal driving strategy. In this project, a suitable model of the Vir'volt electric vehicle involved in the European Shell Eco-Marathon is obtained. The unknown parameters involved in the vehicle dynamics are estimated using Parameter identification from experimental data. The identified dynamics is used to derive an optimal driving strategy that is intended to be tracked on-line during the driving task. The tracking task is subject to time-varying polytopic constraint on the input and/or the state. A MPC-based tracking strategy that uses an homothetic transformation as a suitable time-varying invariant set is used. The time-varying invariant set guarantees the asymptotic stability of the control law. The problem of the MPC tracking for Linear Parametric Varying (LPV) systems is introduced. A new explicit MPC strategy for LPV systems is developed. This strategy uses a Parameter dependent Lyapunov Function (PDLF) to involve explicitly the time-varying parameter in the control law and so it reduces conservatism. A benchmark is used to test the performances of the optimal driving strategy and the explicit MPC tracking strategy. Finally, a robust adaptive technique with on-line identification of the dynamics is has been proposed and tested in the race showing good performances of the adaptive driving strategy
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Manrique, Espindola Dolly Tatiana. "Commande optimale d’une voiture électrique à faible consommation sous contraintes temps réel." Electronic Thesis or Diss., Université de Lorraine, 2014. http://www.theses.fr/2014LORR0198.
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Le problème de l'efficacité énergétique dans le domaine des transports a comme principal défi savoir comment utiliser la source d'énergie pour que l'efficacité énergétique puisse être maximisée, c'est-à-dire comment le véhicule doit être conduit de telle sorte que la quantité minimale d’énergie est utilisée. Ce problème est le principal problème considéré dans cette thèse. Le véhicule est un prototype impliqué dans la course européenne Shell Eco-Marathon. La dynamique du véhicule est d'abord obtenu par l'identification expérimentale des paramètres. Une stratégie en boucle ouverte de conduite optimale en termes de consommation électrique est calculée. Plusieurs approches ont été étudiées pour le suivi de la référence optimale (stratégie de conduite optimale). Ces approches doivent prendre en compte les ressources limitées en taille mémoire et capacité de calcul. Une commande prédictive (MPC) basée sur la dynamique linéarisée est tout d'abord synthétisée. Le problème de poursuite nécessite une MPC avec contraintes variant dans le temps. La stabilité et la convergence de la commande prédictive sont prouvées à l'aide du formalisme des ensembles invariants. En troisième partie, à partie du modèle LPV, une adaptation de techniques standards basées sur des fonctions de Lyapunov quadratiques et à paramètres variants avec calculs hors-ligne est proposée. Elle est implémentée sur un banc de test. Enfin, une technique adaptative robuste avec identification en ligne de la dynamique est proposée et implémentée dans le véhicule. Cette technique a été testée et validée en course. Les résultats expérimentaux obtenus montrent de bonnes performances de la stratégie de conduite<br>In the field of transportation, the research on energy efficiency has been carried out for few decades by the automotive industry, where one of the main objectives is to reduce the energetic consumption. This particular problem can be rephrased as how the vehicle must be driven so that the minimum quantity of energy is used. This is the optimal driving strategy. In this project, a suitable model of the Vir'volt electric vehicle involved in the European Shell Eco-Marathon is obtained. The unknown parameters involved in the vehicle dynamics are estimated using Parameter identification from experimental data. The identified dynamics is used to derive an optimal driving strategy that is intended to be tracked on-line during the driving task. The tracking task is subject to time-varying polytopic constraint on the input and/or the state. A MPC-based tracking strategy that uses an homothetic transformation as a suitable time-varying invariant set is used. The time-varying invariant set guarantees the asymptotic stability of the control law. The problem of the MPC tracking for Linear Parametric Varying (LPV) systems is introduced. A new explicit MPC strategy for LPV systems is developed. This strategy uses a Parameter dependent Lyapunov Function (PDLF) to involve explicitly the time-varying parameter in the control law and so it reduces conservatism. A benchmark is used to test the performances of the optimal driving strategy and the explicit MPC tracking strategy. Finally, a robust adaptive technique with on-line identification of the dynamics is has been proposed and tested in the race showing good performances of the adaptive driving strategy
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Ahmed, Mohamed Salem. "Contribution à la statistique spatiale et l'analyse de données fonctionnelles." Thesis, Lille 3, 2017. http://www.theses.fr/2017LIL30047/document.
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Ce mémoire de thèse porte sur la statistique inférentielle des données spatiales et/ou fonctionnelles. En effet, nous nous sommes intéressés à l’estimation de paramètres inconnus de certains modèles à partir d’échantillons obtenus par un processus d’échantillonnage aléatoire ou non (stratifié), composés de variables indépendantes ou spatialement dépendantes.La spécificité des méthodes proposées réside dans le fait qu’elles tiennent compte de la nature de l’échantillon étudié (échantillon stratifié ou composé de données spatiales dépendantes).Tout d’abord, nous étudions des données à valeurs dans un espace de dimension infinie ou dites ”données fonctionnelles”. Dans un premier temps, nous étudions les modèles de choix binaires fonctionnels dans un contexte d’échantillonnage par stratification endogène (échantillonnage Cas-Témoin ou échantillonnage basé sur le choix). La spécificité de cette étude réside sur le fait que la méthode proposée prend en considération le schéma d’échantillonnage. Nous décrivons une fonction de vraisemblance conditionnelle sous l’échantillonnage considérée et une stratégie de réduction de dimension afin d’introduire une estimation du modèle par vraisemblance conditionnelle. Nous étudions les propriétés asymptotiques des estimateurs proposées ainsi que leurs applications à des données simulées et réelles. Nous nous sommes ensuite intéressés à un modèle linéaire fonctionnel spatial auto-régressif. La particularité du modèle réside dans la nature fonctionnelle de la variable explicative et la structure de la dépendance spatiale des variables de l’échantillon considéré. La procédure d’estimation que nous proposons consiste à réduire la dimension infinie de la variable explicative fonctionnelle et à maximiser une quasi-vraisemblance associée au modèle. Nous établissons la consistance, la normalité asymptotique et les performances numériques des estimateurs proposés.Dans la deuxième partie du mémoire, nous abordons des problèmes de régression et prédiction de variables dépendantes à valeurs réelles. Nous commençons par généraliser la méthode de k-plus proches voisins (k-nearest neighbors; k-NN) afin de prédire un processus spatial en des sites non-observés, en présence de co-variables spatiaux. La spécificité du prédicteur proposé est qu’il tient compte d’une hétérogénéité au niveau de la co-variable utilisée. Nous établissons la convergence presque complète avec vitesse du prédicteur et donnons des résultats numériques à l’aide de données simulées et environnementales.Nous généralisons ensuite le modèle probit partiellement linéaire pour données indépendantes à des données spatiales. Nous utilisons un processus spatial linéaire pour modéliser les perturbations du processus considéré, permettant ainsi plus de flexibilité et d’englober plusieurs types de dépendances spatiales. Nous proposons une approche d’estimation semi paramétrique basée sur une vraisemblance pondérée et la méthode des moments généralisées et en étudions les propriétés asymptotiques et performances numériques. Une étude sur la détection des facteurs de risque de cancer VADS (voies aéro-digestives supérieures)dans la région Nord de France à l’aide de modèles spatiaux à choix binaire termine notre contribution<br>This thesis is about statistical inference for spatial and/or functional data. Indeed, weare interested in estimation of unknown parameters of some models from random or nonrandom(stratified) samples composed of independent or spatially dependent variables.The specificity of the proposed methods lies in the fact that they take into considerationthe considered sample nature (stratified or spatial sample).We begin by studying data valued in a space of infinite dimension or so-called ”functionaldata”. First, we study a functional binary choice model explored in a case-controlor choice-based sample design context. The specificity of this study is that the proposedmethod takes into account the sampling scheme. We describe a conditional likelihoodfunction under the sampling distribution and a reduction of dimension strategy to definea feasible conditional maximum likelihood estimator of the model. Asymptotic propertiesof the proposed estimates as well as their application to simulated and real data are given.Secondly, we explore a functional linear autoregressive spatial model whose particularityis on the functional nature of the explanatory variable and the structure of the spatialdependence. The estimation procedure consists of reducing the infinite dimension of thefunctional variable and maximizing a quasi-likelihood function. We establish the consistencyand asymptotic normality of the estimator. The usefulness of the methodology isillustrated via simulations and an application to some real data.In the second part of the thesis, we address some estimation and prediction problemsof real random spatial variables. We start by generalizing the k-nearest neighbors method,namely k-NN, to predict a spatial process at non-observed locations using some covariates.The specificity of the proposed k-NN predictor lies in the fact that it is flexible and allowsa number of heterogeneity in the covariate. We establish the almost complete convergencewith rates of the spatial predictor whose performance is ensured by an application oversimulated and environmental data. In addition, we generalize the partially linear probitmodel of independent data to the spatial case. We use a linear process for disturbancesallowing various spatial dependencies and propose a semiparametric estimation approachbased on weighted likelihood and generalized method of moments methods. We establishthe consistency and asymptotic distribution of the proposed estimators and investigate thefinite sample performance of the estimators on simulated data. We end by an applicationof spatial binary choice models to identify UADT (Upper aerodigestive tract) cancer riskfactors in the north region of France which displays the highest rates of such cancerincidence and mortality of the country
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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.
Full textAbstract:
Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
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Tsai, Ju-Pien, and 蔡秉儒. "LMI-Based Fuzzy Model Predictive Control for Nonlinear Systems-Using NeuralNetworks to Update Grade Functions." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/17972160811849544037.
Full textAbstract:
碩士<br>中原大學<br>電機工程研究所<br>94<br>Model predictive control (MPC) is also known as receding horizon control (RHC) or moving horizon control (MHC). It is the most popular industrial control strategy, based on the idea of optimizing an objective function at each sampling. Although, many physical models are nonlinear, most researches on this issue are limited to linear systems. Recently, the Takagi-Sugeno (T-S) fuzzy
approach has been used to model nonlinear systems using the decomposition of a nonlinear system into a set of linear subsystems. In this thesis, we will combine the T-S fuzzy model with the MPC strategy to deal with nonlinear systems. Since the
grade functions of the fuzzy controller are independent to the system, in our control design we will update the grade functions via neural networks to achieve the better system performance. In addition, we will discuss the output tracking control based on output feedback design. To this end, the new concept, virtual-
desired-variable (VDV) synthesis will be presented. The advantage of using the VDV synthesis is fully illustrated when we consider
the example of the truck-trailer system. Although the system is only with a single input, we can control the different outputs via
a unified manner. Therefore, we can switch the desired output arbitrarily without changing the control structure. Finally, observer-based control design is proposed to cope with the
immeasurable state variables. For the most parts we focus on a common feature held by many physical systems where their
membership functions of fuzzy sets satisfy a Lipschitz-like property. Based on this setting, control gains and observer gains
can be designed separately. Two different types of systems, H'enon map and truck-trailer systems are considered to demonstrate the design procedure using satisfactory numerical simulation results.
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Ju-Pien, Tsai. "LMI-Based Fuzzy Model Predictive Control for Nonlinear Systems-Using Neural Networks to Update Grade Functions." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0017-1901200710303002.
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Chang, Shuo-Feng, and 張碩峰. "Implementation of a Matrix-Converter Based IPMSM Speed Control System with Predictive Controller and Fault-Tolerant Function." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/hdvzyc.
Full textAbstract:
碩士<br>國立臺灣科技大學<br>電機工程系<br>106<br>This thesis investigates a fault-tolerant matrix-converter interior permanent-magnet synchronous motor speed-control system, which uses a predictive controller to improve the dynamic responses. In addition, fault detection and fault-tolerant methods, including current sensors and encoder faults, are proposed to enhance the transient responses, load responses and reliability by replacing the faulty feedback states with the estimated states of the estimator when the sensors are faulty.
A digital signal processor, TMS320LF2407A, is used as a control center to execute the state estimation, control and fault-tolerant methods, which are developed to increase the system performance. Experimental results can validate the correctness and feasibility of the proposed system.