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Stable Adaptive Neural Network Control (The International Series on Asian Studies in Computer and Information Science)
Stable Adaptive Neural Network Control - The International Series on Asian Studies in Computer and Information Science
Author: S.S. Ge, C.C. Hang, T.H. Lee, Tao Zhang
While neural network control has been successfully applied in various practical applications, many important issues, such as stability, robustness, and performance, have not been extensively researched for neural adaptive systems. Motivated by the need for systematic neural control strategies for nonlinear systems, Stable Adaptive Neura...  more » offers an in-depth study of stable adaptive control designs using approximation-based techniques, and presents rigorous analysis for system stability and control performance. Both linearly parameterized and multi-layer neural networks (NN) are discussed and employed in the design of adaptive NN control systems for completeness. Stable adaptive NN control has been thoroughly investigated for several classes of nonlinear systems, including nonlinear systems in Brunovsky form, nonlinear systems in strict-feedback and pure-feedback forms, nonaffine nonlinear systems, and a class of MIMO nonlinear systems. In addition, the developed design methodologies are not only applied to typical example systems, but also to real application-oriented systems, such as the variable length pendulum system, the underactuated inverted pendulum system and nonaffine nonlinear chemical processes (CSTR).
ISBN-13: 9781441949325
ISBN-10: 1441949321
Publication Date: 11/2/2010
Pages: 298
Edition: 1st Edition.
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Publisher: Springer
Book Type: Paperback
Other Versions: Hardcover
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