Predictive Control of Nonlinear System Based on Neural Networks
Predictive Control of Nonlinear Systems Using Feedback Linearisation Based on Dynamic Neural Networks
Seiten
2011
LAP Lambert Acad. Publ. (Verlag)
978-3-8443-0009-3 (ISBN)
LAP Lambert Acad. Publ. (Verlag)
978-3-8443-0009-3 (ISBN)
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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.
Sprache | englisch |
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Maße | 150 x 220 mm |
Gewicht | 276 g |
Themenwelt | Technik ► Elektrotechnik / Energietechnik |
ISBN-10 | 3-8443-0009-0 / 3844300090 |
ISBN-13 | 978-3-8443-0009-3 / 9783844300093 |
Zustand | Neuware |
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