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
* 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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : New. Extremum seeking is a method of adaptive control outside the classical paradigm or model reference and related schemes. The unique feature of extremum seeking as an optimization tool is that is is an on-line methodology, performed by feedback, and with the ability to achieve rapid convergence. Num Pages: 248 pages, bibliography, index. BIC Classification: PBU. Category: (P) Professional & Vocational. Dimension: 235 x 165 x 16. Weight in Grams: 474. . 2003. 1st Edition. Hardcover. . . . . N° de réf. du vendeur V9780471468592
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Buch. Etat : Neu. Neuware - An up-close look at the theory behind and application of extremum seekingOriginally 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\* Demonstrates the immense potential of this methodology for future theory development and applicationsReal-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. N° de réf. du vendeur 9780471468592
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