Details

Title Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach
Author Yedavalli, Rama K
Binding Hardback
Condition Used - Good
Pages 204
Volumes 1
Language ENG
Publisher Springer
Publication date 2013-12-06
Illustrated Yes
Features Bibliography, Illustrated
Bookseller's Inventory # 1461491312.G
ISBN 9781461491316 / 1461491312
Weight 0.9 lbs (0.41 kg)
Dimensions 9.2 x 6.3 x 0.7 in (23.37 x 16.00 x 1.78 cm)
Category Technology & Industrial Arts
Library of Congress subjects Robust control, System theory
Library of Congress Catalogue Number 2013954668
Dewey Decimal Code 519
Quantity available 1

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From the publisher

This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the "real world" system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach.

This book also:

Presents and formulates the robustness problem in a linear state space model framework.

Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering.

Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches.

Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.

From the rear cover

This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the "real world" system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach.

This book also:

Presents and formulates the robustness problem in a linear state space model framework

Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering

Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches

Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.

About the author

Professor Yedavalli has been teaching the robust control course at Ohio State for many years. Having not found a text that meets his needs, he developed his own course notes. The course in robust control is offered at the first year graduate level at universities with a graduate level engineering program. Professor Yedavalli believes that there is a need for a book that concentrates on the time domain state space approach and uses quadratic stability (lyapunov based) methodology. The books currently available take a frequency domain (transfer function based) approaches such as H-infinity and Mu synthesis.

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