This text presents an approach developed by the author, to handle some of the most common types of component imperfections encountered in industrial automation, consumer electronics, and defence and transportation systems. Series: Adaptive and Learning Systems for Signal Processing, Communications and Control Series. Num Pages: 294 pages, index. BIC Classification: TGPQ; TJFM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 241 x 165 x 26. Weight in Grams: 586. . 1996. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Bestandsnummer des Verk�ufers V9780471156543

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Bibliografische Details

Titel: Adaptive Control of Systems with Actuator and Sensor Nonlinearities
Verlag: John Wiley and Sons Ltd
Erscheinungsjahr: 1996
Sprache: Englisch
ISBN-10: 047115654X
ISBN-13: 9780471156543
Einband: Hardcover
Zustand: New

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An in-depth examination of intelligent approaches to increasing the accuracy of a variety of system components. Utilizing a unified, adaptive, inverse approach, the book offers electrical, mechanical, chemical, aeronautical and computer engineers methods for controlling many of the "hard" nonlinearities of frequently-employed control systems such as dead-zone, backlash and hysteresis. Discusses such nonlinearities at both the input and output points of a linear part and within both continuous time designs and discrete time designs.

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GANG TAO received his PhD in electrical engineering from the University of Southern California in 1989. He is currently an assistant professor in the Department of Electrical Engineering at the University of Virginia. PETAR V. Kokotovi has been Director of the Center for Control Engineering and Computation at the University of California, Santa Barbara, since 1991. Previously, he was with the University of Illinois, where he held the Grainger Chair. He is a member of the National Academy of Engineering. His recognition as a leading authority in control theory theory includes the triennial Quazza Medal by IFAC in 1990 and the 1995 IEEE Control Systems Award.

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