Real Time Optimization by Extremum–Seeking Control
Seiten
2004
John Wiley & Sons Inc (Hersteller)
978-0-471-66978-4 (ISBN)
John Wiley & Sons Inc (Hersteller)
978-0-471-66978-4 (ISBN)
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Presents the theoretical foundations and applications of extremum seeking method of real-time optimization. Written by authorities in the field and pioneers in adaptive nonlinear control systems, this book is useful for both students and professionals in various areas of engineering, such as electrical, mechanical, aerospace, and biomedical.
This book offers an up-close look at the theory behind and application of extremum seeking. Originally developed as a method of adaptive control for hard-to-model systems, extremum seeking solves some of the same problems as today's neural network techniques, but in a more rigorous and practical way. Following the resurgence in popularity of extremum-seeking control in aerospace and automotive engineering, "Real-Time Optimization by Extremum-Seeking Control" presents the theoretical foundations and selected applications of this method of real-time optimization. Written by authorities in the field and pioneers in adaptive nonlinear control systems, this book presents both significant theoretic value and important practical potential.
Filled with in-depth insight and expert advice, "Real-Time Optimization by Extremum-Seeking Control": develops optimization theory from the points of dynamic feedback and adaptation; builds a solid bridge between the classical optimization theory and modern feedback and adaptation techniques; provides a collection of useful tools for problems in this complex area; presents numerous applications of this powerful methodology; and demonstrates the immense potential of this methodology for future theory development and applications. "Real-Time Optimization by Extremum-Seeking Control" is an important resource for both students and professionals in all areas of engineering - electrical, mechanical, aerospace, chemical, biomedical - and is also a valuable reference for practicing control engineers.
This book offers an up-close look at the theory behind and application of extremum seeking. Originally developed as a method of adaptive control for hard-to-model systems, extremum seeking solves some of the same problems as today's neural network techniques, but in a more rigorous and practical way. Following the resurgence in popularity of extremum-seeking control in aerospace and automotive engineering, "Real-Time Optimization by Extremum-Seeking Control" presents the theoretical foundations and selected applications of this method of real-time optimization. Written by authorities in the field and pioneers in adaptive nonlinear control systems, this book presents both significant theoretic value and important practical potential.
Filled with in-depth insight and expert advice, "Real-Time Optimization by Extremum-Seeking Control": develops optimization theory from the points of dynamic feedback and adaptation; builds a solid bridge between the classical optimization theory and modern feedback and adaptation techniques; provides a collection of useful tools for problems in this complex area; presents numerous applications of this powerful methodology; and demonstrates the immense potential of this methodology for future theory development and applications. "Real-Time Optimization by Extremum-Seeking Control" is an important resource for both students and professionals in all areas of engineering - electrical, mechanical, aerospace, chemical, biomedical - and is also a valuable reference for practicing control engineers.
Kartik B. Ariyur is a research scientist at Honeywell Aerospace Electronic Systems in Minneapolis, Minnesota. Miroslav Krstic is Professor of Mechanical and Aerospace Engineering at the University of California, San Diego.
| Erscheint lt. Verlag | 26.3.2004 |
|---|---|
| Verlagsort | New York |
| Sprache | englisch |
| Gewicht | 10 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| ISBN-10 | 0-471-66978-4 / 0471669784 |
| ISBN-13 | 978-0-471-66978-4 / 9780471669784 |
| Zustand | Neuware |
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