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Gang Tao - Adaptive Control of Systems with Actuator and Sensor Nonlinearities - 9780471156543 - V9780471156543
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Adaptive Control of Systems with Actuator and Sensor Nonlinearities

€ 208.24
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Description for Adaptive Control of Systems with Actuator and Sensor Nonlinearities Hardcover. 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.
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.

Product Details

Format
Hardback
Publication date
1996
Publisher
John Wiley and Sons Ltd United States
Number of pages
294
Condition
New
Series
Adaptive and Learning Systems for Signal Processing, Communications and Control Series
Number of Pages
294
Place of Publication
, United States
ISBN
9780471156543
SKU
V9780471156543
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50

About Gang Tao
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 ... Read more

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