Predictive Control of Nonlinear System Based on Neural Networks: Predictive Control of Nonlinear Systems Using Feedback Linearisation Based on Dynamic Neural Networks - Couverture souple

Deng, Jiamei

 
9783844300093: Predictive Control of Nonlinear System Based on Neural Networks: Predictive Control of Nonlinear Systems Using Feedback Linearisation Based on Dynamic Neural Networks
Couverture souple
ISBN 10 : 3844300090 ISBN 13 : 9783844300093
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

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.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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.

Biographie de l'auteur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3844300090
ISBN 13 
9783844300093
Reliure
Broché
Nombre de pages
200
Coordonnées du fabricant
non disponible
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