Relevant bibliographies by topics / Predictive functional control

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Predictive functional control'

Author: Grafiati
Published: 3 June 2025
Last updated: 19 July 2025

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Journal articles on the topic "Predictive functional control"

1

Guo, Jianguo, Guoqing Wang, Zongyi Guo, and Jun Zhou. "Augmented predictive functional control for missile autopilot design." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 10 (2016): 1794–803. http://dx.doi.org/10.1177/0954410016675892.

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In this paper, an augmented predictive functional control approach is investigated to design a missile autopilot system, which can be expressed as a linear model with state-dependent coefficient matrices. A novel performance index depending on the reference trajectory, the output prediction and the set-point is proposed to improve the closed-loop dynamic performance. An augmented predictive functional control strategy is designed based on the proposed index and the stability is proven by using the Z-transform. In order to demonstrate the performance of the proposed approach, numerical simulations comparing the predictive functional control in the missile autopilot system are performed. Finally, results from comprehensive simulations are presented to evaluate the proposed approach in the presence of input constraints and abrupt disturbances.
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Haber, Robert, Mirco Kreutz, and Khaled Zabet. "Predictive Functional Control: Algorithmus und Testbetrieb." atp edition - Automatisierungstechnische Praxis 53, no. 04 (2011): 22. http://dx.doi.org/10.17560/atp.v53i04.196.

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Haber, Robert, Mirco Kreutz, and Khaled Zabet. "Predictive Functional Control: Algorithmus und Testbetrieb." atp magazin 53, no. 04 (2013): 22–33. http://dx.doi.org/10.17560/atp.v53i04.2124.

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Prädiktive (vorausschauende) Regelungen werden vor allem für komplexe Optimalwertregelungen eingesetzt. Die vorgestellte PFC-Regelung (Predictive Functional Control) bietet Algorithmen für Ein- oder Zweigrößensysteme, welche in speicherprogrammierbaren Steuerungen und Prozessleitsystemen einfach implementiert werden können. Der Algorithmus berücksichtigt die vorhandenen Begrenzungen und vermeidet das Integrator-Windup. Der textdata zeigt grundlegende Eigenschaften von PFC sowie Implementierungsmöglichkeiten in das Prozessleitsystem Simatic PCS7 auf.
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Zhang, Zhiming, John Anthony Rossiter, Lei Xie, and Hongye Su. "Predictive functional control for integrator systems." Journal of the Franklin Institute 357, no. 7 (2020): 4171–86. http://dx.doi.org/10.1016/j.jfranklin.2020.01.026.

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Dovžan, Dejan, and Igor Škrjanc. "Control of mineral wool thickness using predictive functional control." Robotics and Computer-Integrated Manufacturing 28, no. 3 (2012): 344–50. http://dx.doi.org/10.1016/j.rcim.2011.10.004.

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Hashimoto, Yusuke, Toshiyuki Satoh, Jun Ya Nagase, and Norihiko Saga. "Predictive Functional Control for a Pneumatic Cylinder." Applied Mechanics and Materials 789-790 (September 2015): 932–38. http://dx.doi.org/10.4028/www.scientific.net/amm.789-790.932.

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Japan is becoming a super-aging society, with a population decrease and a shortage of young workers. Mechanisms using pneumatic cylinders are therefore expected to be useful to perform tasks such as day-to-day work support for elderly people. However, pneumatic cylinder includes large dead time. Thereby, traditional control system is complex, such as adding Smith compensation. Therefore, we use Predictive Functional Control (PFC). This control system is not complex even if plant includes dead time. This study evaluates the performance of force and position control systems using a pneumatic cylinder and PFC. We compare the PFC scheme with the PID control and show that PFC achieves better performance than PID control.
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Preglej, Aleksander, Igor Steiner, and Sašo Blažič. "Multivariable Predictive Functional Control of an Autoclave." Strojniški vestnik – Journal of Mechanical Engineering 59, no. 2 (2013): 89–96. http://dx.doi.org/10.5545/sv-jme.2012.617.

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Tang, Wei-Qiang, and Yuan-Li Cai. "Predictive Functional Control-Based Missile Autopilot Design." Journal of Guidance, Control, and Dynamics 35, no. 5 (2012): 1450–55. http://dx.doi.org/10.2514/1.56329.

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Vivas, Andrés, and Philippe Poignet. "Predictive functional control of a parallel robot." Control Engineering Practice 13, no. 7 (2005): 863–74. http://dx.doi.org/10.1016/j.conengprac.2004.10.001.

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Liang, Xiao Ming, and Hui Fang Wang. "The Application of New Predictive Functional Control in the Converter Gas Recovery System." Applied Mechanics and Materials 685 (October 2014): 289–93. http://dx.doi.org/10.4028/www.scientific.net/amm.685.289.

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In view of the characteristics of the converter differential pressure control system are nonlinear, large delay, uncertainty and large disturbance, the traditional PID control is strict with process model, which can't satisfy the requirement of tracking set point and suppressing disturbance. Predictive functional control is not strict with process model, it has good robustness, but has problem of large amount of calculation. By introducing the output prediction error and the output increment prediction error in the performance index function, a new predictive functional control algorithm with the PID structure is proposed, which combines ability of dealing with delay and robust for predictive function control with ability of favorable anti-interference and fast tracking for PID control. The simulation shows that the control strategy is feasible, and can obviously improve the dynamic quality and anti-interference ability of the converter differential pressure control system.
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Dissertations / Theses on the topic "Predictive functional control"

1

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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Books on the topic "Predictive functional control"

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Richalet, Jacques, and Donal O'Donovan. Predictive Functional Control. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-493-5.

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Donal, O'Donovan, ed. Predictive functional control: Principles and industrial applications. Springer, 2009.

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Christofides, Panagiotis D. Networked and Distributed Predictive Control: Methods and Nonlinear Process Network Applications. Springer-Verlag London Limited, 2011.

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Zhang, Xin, Jinsong He, Hao Ma, Zhixun Ma, and Xiaohai Ge. Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7191-4.

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Manning, Carol A. Prediction of seccess [i.e., success] in FAA air traffic control field training as a function of selection and screening test performance. Office of Aviation Medicine, Federal Aviation Administration, 1989.

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Manning, Carol A. Prediction of seccess [i.e., success] in FAA air traffic control field training as a function of selection and screening test performance. Office of Aviation Medicine, Federal Aviation Administration, 1989.

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Kazakova, Nataliya. Financial security of the company. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1908969.

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The textbook provides theoretical and practical training of business analysts on the financial security of companies. Considers the regulatory legal and methodological basis for the diagnosis of bankruptcy of organizations, as well as corporate fraud as a type of economic crimes; analytical tools for assessing the level of financial security based on a risk-oriented approach, the basics of building an internal financial security control system, including monitoring of the company's business processes affecting its financial security, as well as methods for assessing the risks of corporate fraud. The methods of diagnostics of the processes of companies' activities that contribute to improving their financial security through the introduction of a comprehensive digital environment, predictive analytics and big data technology into the control and diagnostic processes of business management are considered. Each chapter includes knowledge assessment questions, tests and situational tasks.&#x0D; It complies with the federal state educational standards of higher education of the latest generation, is focused on the competence model of the main professional educational programs, and also provides the functionality (requirements for labor functions) of employees laid down in the state professional standard "Business Analyst".&#x0D; For master's degree students studying in the areas of 38.04.01 "Economics", 38.04.02 "Management", 38.04.08 "Finance and Credit".
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Box, George E. P. Time series analysis: Forecasting and control. 4th ed. John Wiley, 2008.

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Box, George E. P. Time series analysis: Forecasting and control. 3rd ed. Prentice Hall, 1994.

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Box, George E. P. Time series analysis: Forecasting and control. 4th ed. John Wiley, 2008.

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Book chapters on the topic "Predictive functional control"

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Zhang, Ridong, Anke Xue, and Furong Gao. "Predictive Functional Control Based on Extended State Space Model." In Model Predictive Control. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0083-7_3.

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Zhang, Ridong, Anke Xue, and Furong Gao. "Predictive Functional Control Based on Extended Non-minimal State Space Model." In Model Predictive Control. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0083-7_5.

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Wu, Jianguo, and Minrui Fei. "The Networked Control Systems Based on Predictive Functional Control." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-37275-2_136.

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Peng, Daogang, Jiajun Lin, Yue Wu, and Hao Zhang. "Research of Networked Control System Based on Predictive Functional Control." In AsiaSim 2012. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34390-2_2.

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Szymanski, Dariusz, Matthias Scharrer, Georg Macher, Eric Armengaud, and Holger Schmidt. "Model-Based Functional Safety Engineering." In Comprehensive Energy Management - Safe Adaptation, Predictive Control and Thermal Management. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57445-5_2.

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Tang, Weiqiang, Yongda Qi, Mengke Guo, and Haiyan Gao. "Model Correction-Based Multivariable Predictive Functional Control for Uncertain Nonlinear Systems." In Nonlinear Dynamics and Control. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34747-5_27.

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Aftab, Muhammad Saleheen, John Anthony Rossiter, and Zhiming Zhang. "Predictive Functional Control for Unstable First-Order Dynamic Systems." In Lecture Notes in Electrical Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58653-9_2.

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Wu, Wei, Qiang Yang, and Wenjun Yan. "On the Design of Incremental Predictive Functional Control Algorithm." In Electrical, Information Engineering and Mechatronics 2011. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2467-2_2.

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Xin-fang, Zhang, Wang Cheng-li, Su Xian-hua, and Wang Qiu-jin. "Nonlinear Predictive Functional Control Based on Support Vector Machine." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1839-5_82.

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Zhi, Haisu. "Predictive Functional Control for Tension of Cold Continuous Rolling Mill." In Lecture Notes in Electrical Engineering. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4847-0_18.

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Conference papers on the topic "Predictive functional control"

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Abdullah, Muhammad, and John Anthony Rossiter. "Utilising Laguerre function in predictive functional control to ensure prediction consistency." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737639.

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Abdullah, Muhammad, and John Anthony Rossiter. "A Formal Sensitivity Analysis for Laguerre Based Predictive Functional Control." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516849.

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Sidorov, A. V. "APPLICATION OF PREDICTIVE ANALYTICS FOR MULTIPARAMETER TECHNOLOGICAL PROCESS MONITORING AND CONTROL." In Actual problems of physical and functional electronics. Ulyanovsk State Technical University, 2024. http://dx.doi.org/10.61527/appfe-2024.371-372.

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Predictive analytics as a tool for technological process prediction is reviewed. Foundations, including surrogate models and manifold modeling, as a solution to the problem of applying control charts are specified.
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Abdullah, Muhammad, and John Anthony Rossiter. "Alternative Method for Predictive Functional Control to Handle an Integrating Process." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516787.

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Xu, Mingzhu, Xiaoli Li, Heping Liu, and Yanshuang Hao. "Adaptive Predictive Functional Control with Stochastic Search." In 2006 IEEE International Conference on Information Acquisition. IEEE, 2006. http://dx.doi.org/10.1109/icia.2006.305950.

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Ouali, Nassima, Hocine Lehouche, Abdelhakim Belkaid, Ilhami Colak, Cylia Ibaouene, and A. yazid Achour. "Predictive Functional Control for Photovoltaic System Optimization." In 2023 11th International Conference on Smart Grid (icSmartGrid). IEEE, 2023. http://dx.doi.org/10.1109/icsmartgrid58556.2023.10170895.

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Amiri, Enayat, Mohammad Haeri, and Saeed Adelipour. "Secret Sharing Implementation of Predictive Functional Control." In 2023 31st International Conference on Electrical Engineering (ICEE). IEEE, 2023. http://dx.doi.org/10.1109/icee59167.2023.10334819.

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Zhang Jiaying and Wu Xinmei. "Predictive functional control simulation of boiler combustion control system." In 2011 Second International Conference on Mechanic Automation and Control Engineering (MACE). IEEE, 2011. http://dx.doi.org/10.1109/mace.2011.5986977.

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Waghmare, Amit Vijay, and Surender Kannaiyan. "Real Time Heat Exchanger Control Using Predictive Functional Control." In 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2018. http://dx.doi.org/10.1109/icccnt.2018.8494114.

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Kirsch, Nicholas A., Naji A. Alibeji, and Nitin Sharma. "Nonlinear Model Predictive Control of Functional Electrical Stimulation." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9762.

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One of the major limitations of functional electrical stimulation (FES) is the rapid onset of muscle fatigue. Minimizing stimulation is the key to decreasing the adverse effects of muscle fatigue caused by FES. Optimal control can be used to compute the minimum amount of stimulation necessary to produce a desired motion. In this paper, a gradient projection-based model predictive controller is used for an approximate optimal control of a knee extension neuroprosthesis. A control Lyapunov function is used as a terminal cost to ensure stability of the model predictive control.
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Reports on the topic "Predictive functional control"

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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.
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Avihingsanon, Yingyos, Jongkonnee Wongpiyabovorn, and Nattiya Hirankarn. Biomarker discovery in systemic lupus erythematosus: genome-methylation approaches : Research report. Chulalongkorn University, 2010. https://doi.org/10.58837/chula.res.2010.15.

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Discovery of novel biomarkers in lupus nephritis Biomarkers are needed for making diagnosis and prognosis. In lupus nephritis, conventional tests like urinalysis or serum creatinine remain inadequate for patient care. In this proposal, we focused on non-invasive tools like blood and urine mRNAs or proteins. We chose candidate genes involving regulatory T-cell, B-lymphocyte signatures or vascular protective factors. Expression of regulatory cell signature (FOXP3) in peripheral blood mononuclear cells is associated with activity of lupus nephritis. We found FOXP3 mRNA levels in PBMCs from patients with active lupus nephritis were significantly lower than inactive lupus nephritis. Expression levels of FOXP3 mRNA were associated with pathological activity index, cellular crescent and fibrinoid necrosis. BLyS and APRIL are B-lymphocyte related cytokines that play an important role in generating and maintaining the mature B-cell pool. In this study, we found blood APRIL correlated with activity of lupus nephritis. Blood APRIL levels could precisely predict failure of standard treatment treatment. APRIL is a potential biomarker for predicting treatment failure. Lastly, we found an expression of VEGF in renal tissue may serve as a molecular marker of renal damage from LN and may be a predictive factor for short-term loss of kidney function in lupus nephritis patients. We proposed that reduction of intra-renal VEGF level caused by losses of podocyte cells. Genetic polymorphism of drug toxicity or pharmacokinetics in SLE patients We began to explore the pharmacokinetics and pharmacogenomics of two important immunosuppressants, azathioprine and mycophenolate. In this study, we report TPMT polymorphisms and TPMT enzyme activity were important predictors of AZA-induced myelosuppression. The tests are available for routine care. Mycophenolic acid (MPA) is active metabolite of mycophenalate. We found MPA levels is important predictor of therapeutic response. The therapeutic drug monitoring is now an important issue of patient care. We found UGT1A9 polymorphism may play a pivotal role in drug metabolisms. Methylation study We examined and compared the methylation levels of long terminal repeats (LTRs) and non-LTR retroelements in normal and SLE CD4+ T lymphocytes, CD8+ T lymphocytes and B lymphocytes. Hypomethylation of LINE-1 but not Alu was found in CD4+ T lymphocytes, CD8+ T lymphocytes, and B lymphocytes of SLE patient. Moreover, when the SLE patients were divided into active and inactive groups, LINE-1 hypomethylation was more significantly distinguished in both CD4+ and CD8+ T lymphocytes of patients from the active SLE group when compared to the controls. Genome-wide scanning using SNP microarrays In this study, we applied case-control association study including pooling genome wide association (GWA) and candidate gene association studies to search for SNPs associated with SLE susceptibility and/or severity. We could not identify any SNPs with distinct p-value or odds ratio from our pooling GWA result due to limited power. We selected IFIX for further study in candidate gene’s part. Besides IFIX, we also focus on MNDA, IFI16 and AIM2 genes which located in the same region and are all IFN-inducible genes. They are important SLE susceptibility genes due to several reasons including 1) genetic mapping from lupus murine model and 2) an upregulated IFN-inducible genes in patients with SLE from microarray studies and 3) IFI16 was identified as new autoantigen for patients with SLE. We genotyped 10 SNPs from these 4 genes and found that SNP within IFIX and IFI16 are independently important.
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Or, Dani, Shmulik Friedman, and Jeanette Norton. Physical processes affecting microbial habitats and activity in unsaturated agricultural soils. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7587239.bard.

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experimental methods for quantifying effects of water content and other dynamic environmental factors on bacterial growth in partially-saturated soils. Towards this end we reviewed critically the relevant scientific literature and performed theoretical and experimental studies of bacterial growth and activity in modeled, idealized and real unsaturated soils. The natural wetting-drying cycles common to agricultural soils affect water content and liquid organization resulting in fragmentation of aquatic habitats and limit hydraulic connections. Consequently, substrate diffusion pathways to soil microbial communities become limiting and reduce nutrient fluxes, microbial growth, and mobility. Key elements that govern the extent and manifestation of such ubiquitous interactions include characteristics of diffusion pathways and pore space, the timing, duration, and extent of environmental perturbations, the nature of microbiological adjustments (short-term and longterm), and spatial distribution and properties of EPS clusters (microcolonies). Of these key elements we have chosen to focus on a manageable subset namely on modeling microbial growth and coexistence on simple rough surfaces, and experiments on bacterial growth in variably saturated sand samples and columns. Our extensive review paper providing a definitive “snap-shot” of present scientific understanding of microbial behavior in unsaturated soils revealed a lack of modeling tools that are essential for enhanced predictability of microbial processes in soils. We therefore embarked on two pronged approach of development of simple microbial growth models based on diffusion-reaction principles to incorporate key controls for microbial activity in soils such as diffusion coefficients and temporal variations in soil water content (and related substrate diffusion rates), and development of new methodologies in support of experiments on microbial growth in simple and observable porous media under controlled water status conditions. Experimental efforts led to a series of microbial growth experiments in granular media under variable saturation and ambient conditions, and introduction of atomic force microscopy (AFM) and confocal scanning laser microscopy (CSLM) to study cell size, morphology and multi-cell arrangement at a high resolution from growth experiments in various porous media. The modeling efforts elucidated important links between unsaturated conditions and microbial coexistence which is believed to support the unparallel diversity found in soils. We examined the role of spatial and temporal variation in hydration conditions (such as exist in agricultural soils) on local growth rates and on interactions between two competing microbial species. Interestingly, the complexity of soil spaces and aquatic niches are necessary for supporting a rich microbial diversity and the wide array of microbial functions in unsaturated soils. This project supported collaboration between soil physicists and soil microbiologist that is absolutely essential for making progress in both disciplines. It provided a few basic tools (models, parameterization) for guiding future experiments and for gathering key information necessary for prediction of biological processes in agricultural soils. The project sparked a series of ongoing studies (at DTU and EPFL and in the ARO) into effects of soil hydration dynamics on microbial survival strategy under short term and prolonged desiccation (important for general scientific and agricultural applications).
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