Model predictive control (MPC) is an important industrial control technique. Most conventional MPC schemes use linear models. However, the use of linear models can result in a serious deterioration of control performance with many types of nonlinear plants. Feedback linearisation is an important nonlinear control technique which can transform a nonlinear system into a linear system. Dynamic neural networks have the ability to approximate multi-input multi-output general nonlinear systems...
Dr. Jiamei Deng is an internationally established researcher, who is currently a Lecturer in Loughborough University in the United Kingdom. Dr. Deng received her Ph.D. degree in Cybernetics from the University of Reading in 2005. She was an Associate Professor in University of Shanghai between 1998 and 2002.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Model predictive control (MPC) is an important industrial control technique. Most conventional MPC schemes use linear models. However, the use of linear models can result in a serious deterioration of control performance with many types of nonlinear plants. Feedback linearisation is an important nonlinear control technique which can transform a nonlinear system into a linear system. Dynamic neural networks have the ability to approximate multi-input multi-output general nonlinear systems and have the differential equation structure. This book presents a hybrid control strategy integrating dynamic neural networks and feedback linearisation into a predictive control scheme. This book can be used as a course textbook, a source for practising control engineers with an interest in nonlinear control techniques and also a reference material for academic researchers in nonlinear control theory. 200 pp. Englisch. Seller Inventory # 9783844300093
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Model predictive control (MPC) is an important industrial control technique. Most conventional MPC schemes use linear models. However, the use of linear models can result in a serious deterioration of control performance with many types of nonlinear plants. Feedback linearisation is an important nonlinear control technique which can transform a nonlinear system into a linear system. Dynamic neural networks have the ability to approximate multi-input multi-output general nonlinear systems and have the differential equation structure. This book presents a hybrid control strategy integrating dynamic neural networks and feedback linearisation into a predictive control scheme. This book can be used as a course textbook, a source for practising control engineers with an interest in nonlinear control techniques and also a reference material for academic researchers in nonlinear control theory. Seller Inventory # 9783844300093
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Deng JiameiDr. Jiamei Deng is an internationally established researcher, who is currently a Lecturer in Loughborough University in the United Kingdom. Dr. Deng received her Ph.D. degree in Cybernetics from the University of Readin. Seller Inventory # 5470525
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