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Full Description
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.
Contents
1. Modelling of Uncertain Systems and the Robust Control Problem. 2. Fundamentals of Stability. 3. Kalman Canonical Decomposition. 4. Singular Value Decomposition. 5. Open-loop Balanced Realization. 6. Reduced Order Models and Symmetric Systems. 7. Variational Calculus and Linear Quadratic Optimal Control. 8. Closed-loop Balanced Realization. 9. Positive-real, Bounded-real, and Negative-imaginary Systems. 10. Enforcing the Positive-real or the Negative-imaginary Property in a Linear Model. 11. H∞ linear control. 12. Linear Matrix Inequalities for Optimal and Robust Control. 13. The Class of Stabilizing Controllers. 14. Formulation and Solution of Matrix Algebraic Problems Through Optimization Problems. 15. Time-delay Systems. Appendix A. Norms. Appendix B. Algebraic Riccati Equations. Appendix C. Invariance under Frequency Transformations.
