Optimal And Robust Control

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Optimal and Robust Control

There are many books on advanced control for specialists, but not many present these topics for non-specialists. Assuming only a basic knowledge of automatic control and signals and systems, this second edition of Optimal and Robust Control offers a straightforward, self-contained handbook of advanced topics and tools in automatic control. The book deals with advanced automatic control techniques, paying particular attention to robustness-the ability to guarantee stability in the presence of uncertainty. It explains advanced techniques for handling uncertainty and optimizing the control loop. It also details analytical strategies for obtaining reduced order models. The authors then propose using the Linear Matrix Inequality (LMI) technique as a unifying tool to solve many types of advanced control problems. Topics covered in the book include, LQR and H∞ approaches Kalman and singular value decomposition Open-loop balancing and reduced order models Closed-loop balancing Positive-real systems, bounded-real systems, and imaginary-negative systems Criteria for stability control Time-delay systems This easy-to-read text presents the essential theoretical background and provides numerous examples and MATLAB® exercises to help the reader efficiently acquire new skills. Written for electrical, electronic, computer science, space, and automation engineers interested in automatic control, this book can also be used for self-study of for a one-semester course in robust control. This fully renewed second edition of the book also includes new fundamental topics such as Lyapunov functions for stability, variational calculus, formulation in terms of optimization problems of matrix algebraic equations, negative-imaginary systems, and time-delay systems.
Optimal and Robust Control

This new edition deals with advanced automatic control techniques, paying particular attention to robustness-the ability to guarantee stability in the presence of uncertainty. It explains advanced techniques for handling uncertainty and optimizing the control loop and details analytical strategies for obtaining reduced order models.
Robust and Optimal Control

Class-tested at major institutions around the world, this work offers complete coverage of robust and H control. It features clear coverage of methodology, and provides detailed treatment of topics including Riccati equations, m theory, H loopshaping and controller reduction.