Stable adaptive control and estimation for nonlinear systems : neural and fuzzy approximator techniques /
A powerful, yet easy-to-use design methodology for the control of nonlinear dynamic systems. A key issue in the design of control systems is proving that the resulting closed-loop system is stable, especially in cases of high consequence applications, where process variations or failure could result...
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| Format: | eBook |
| Language: | English |
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New York :
Wiley,
©2002.
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| Series: | Adaptive and learning systems for signal processing, communications, and control.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | A powerful, yet easy-to-use design methodology for the control of nonlinear dynamic systems. A key issue in the design of control systems is proving that the resulting closed-loop system is stable, especially in cases of high consequence applications, where process variations or failure could result in unacceptable risk. Adaptive control techniques provide a proven methodology for designing stable controllers for systems that may possess a large amount of uncertainty. At the same time, the benefits of neural networks and fuzzy systems are generating much excitement and impressive innovations in almost every engineering discipline. Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques brings together these two different but equally useful approaches to the control of nonlinear systems in order to provide students and practitioners with the background necessary to understand and contribute to this emerging field. The text presents a control methodology that may be verified with mathematical rigor while possessing the flexibility and ease of implementation associated with "intelligent control" approaches. The authors show how these methodologies may be applied to many real-world systems including motor control, aircraft control, industrial automation, and many other challenging nonlinear systems. They provide explicit guidelines to make the design and application of the various techniques a practical and painless process. Design techniques are presented for nonlinear multi-input multi-output (MIMO) systems in state-feedback, output-feedback, continuous or discrete-time, or even decentralized form. To help students and practitioners new to the field grasp and sustain mastery of the material, the book features: Background material on fuzzy systems and neural networks; Step-by-step controller design; Numerous examples; Case studies using "real world" applications; Homework problems and design projects |
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| Physical Description: | 1 online resource (xvii, 545 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 521-539) and index. |
| ISBN: | 0471221139 9780471221135 9780471460978 0471460974 |