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Predictive Control of Nonlinear System Based on Neural Networks: Predictive Control of Nonlinear Systems Using Feedback Linearisation Based on Dynamic Neural Networks - Tapa blanda
Sinopsis
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.
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Reseña del editor
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.
Biografía del autor
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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Predictive Control of Nonlinear System Based on Neural Networks
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844300090
ISBN 13: 9783844300093
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: 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. Nº de ref. del artículo: 5470525
Cantidad disponible: Más de 20 disponibles
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Predictive Control of Nonlinear System Based on Neural Networks
Publicado por
LAP LAMBERT Academic Publishing Feb 2011, 2011
ISBN 10: 3844300090
ISBN 13: 9783844300093
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783844300093
Cantidad disponible: 2 disponibles
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Predictive Control of Nonlinear System Based on Neural Networks : Predictive Control of Nonlinear Systems Using Feedback Linearisation Based on Dynamic Neural Networks
Publicado por
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844300090
ISBN 13: 9783844300093
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783844300093
Cantidad disponible: 1 disponibles
Imagen del vendedor
Predictive Control of Nonlinear System Based on Neural Networks
Publicado por
LAP LAMBERT Academic Publishing Feb 2011, 2011
ISBN 10: 3844300090
ISBN 13: 9783844300093
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 200 pp. Englisch. Nº de ref. del artículo: 9783844300093
Cantidad disponible: 2 disponibles