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The Gradient Based Nonlinear Model Predictive Control System: Stability, Robustness and Real-time Implementation - Couverture souple
Présentation de l'éditeur
A class of nonlinear model predictive control(NMPC) law based on gradient-based iteration is analyzed and implemented real-time in this book. This NMPC law takes only a finite number of Newton steps in each sampling period instead of solving the complete optimal control problem. The key attribute of the NMPC algorithmused here is that it only seeks to reduce the error at the end of the prediction horizon rather than tries to find the optimal solution. This reduces the computation load and allows for real-time implementation. The stability is shown for a class of discrete-time control-affine system that the NMPC has some inherent robustness property with respect to external disturbances and model error. This property follows from the exponential convergence of the predicted state error. The robustness of this NMPC is analyzed and quantified with uncertainties. In addition to simulation examples, the NMPC algorithm is also applied to the swing-up control experiment of a rotary inverted pendulum. We also discuss the implementation strategy, state estimation issue, and experimental results.
Biographie de l'auteur
received B.S in Seoul National University,Korea, M.S in Columbia University,USA, and Ph.D in Rensselaer Polytechnic Institute,USA, 2002. He is working in Digital Printing Division, Samsung Electronics Co., Ltd. His research includes nonlinear model-predictive control, embedded system and HIL simulation for automotive and printing system.
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- ÉditeurVDM Verlag
- Date d'édition2009
- ISBN 10 363921241X
- ISBN 13 9783639212419
- ReliureBroché
- Langueanglais
- Nombre de pages136
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A class of nonlinear model predictive control(NMPC) law based on gradient-based iteration is analyzed and implemented real-time in this book. This NMPC law takes only a finite number of Newton steps in each sampling period instead of solving the complete optimal control problem. The key attribute of the NMPC algorithmused here is that it only seeks to reduce the error at the end of the prediction horizon rather than tries to find the optimal solution. This reduces the computation load and allows for real-time implementation. The stability is shown for a class of discrete-time control-affine system that the NMPC has some inherent robustness property with respect to external disturbances and model error. This property follows from the exponential convergence of the predicted state error. The robustness of this NMPC is analyzed and quantified with uncertainties. In addition to simulation examples, the NMPC algorithm is also applied to the swing-up control experiment of a rotary inverted pendulum. We also discuss the implementation strategy, state estimation issue, and experimental results. N° de réf. du vendeur 9783639212419
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The Gradient Based Nonlinear Model Predictive Control System
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VDM Verlag Dr. Müller, 2009
ISBN 10 : 363921241X
ISBN 13 : 9783639212419
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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jung Sooyongreceived B.S in Seoul National University,Korea, M.S in Columbia University,USA, and Ph.D in Rensselaer Polytechnic Institute,USA, 2002. He is working in Digital Printing Division, Samsung Electronics Co., Ltd. His res. N° de réf. du vendeur 4967613
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The Gradient Based Nonlinear Model Predictive Control System: Stability, Robustness and Real-time Implementation
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VDM Verlag, 2009
ISBN 10 : 363921241X
ISBN 13 : 9783639212419
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