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Predictive Control of Nonlinear System Based on Neural Networks



Год выпуска: 2011
Автор: Jiamei Deng
Издательство: LAP Lambert Academic Publishing
Страниц: 200
ISBN: 9783844300093
Описание
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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Елена
Марина, спасибо большое за проделанную работу!!! Я защитила диплом после вашего сопровождения на 5!