Optimal and Robust Control: Advanced Topics with MATLAB®
Autor Luigi Fortuna, Mattia Frasca, Arturo Buscarinoen Limba Engleză Paperback – 29 ian 2024
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 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.
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Paperback (1) | 317.58 lei 6-8 săpt. | |
CRC Press – 29 ian 2024 | 317.58 lei 6-8 săpt. | |
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Specificații
ISBN-13: 9781032053011
ISBN-10: 1032053011
Pagini: 322
Ilustrații: 194
Dimensiuni: 156 x 234 mm
Greutate: 0.7 kg
Ediția:2
Editura: CRC Press
Colecția CRC Press
ISBN-10: 1032053011
Pagini: 322
Ilustrații: 194
Dimensiuni: 156 x 234 mm
Greutate: 0.7 kg
Ediția:2
Editura: CRC Press
Colecția CRC Press
Cuprins
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.
Notă biografică
Luigi Fortuna is a Full Professor of System Theory with the Università degli Studi di Catania, Catania, Italy. He has published more than 600 scientific papers regarding robust control, nonlinear science and complexity, chaos, cellular neural networks, softcomputing strategies for control and robotics, micronanosensor and smart devices for control, and nanocellular neural networks modeling.
Mattia Frasca is presently as Associate Professor at the University of Catania, Italy and teaches Process Control and Complex Adaptive Systems. His scientific interests include linear systems, nonlinear dynamics, analysis and control of complex systems, and bio-inspired robotics.
Arturo Buscarino is currently a researcher in Automatic Control at the University of Catania, Italy. He is IEEE Senior Member. His scientific interests include nonlinear circuits and systems, chaos and synchronization, memristors, fuzzy logic, control systems, Cellular Nonlinear Networks, and plasma engineering.
Mattia Frasca is presently as Associate Professor at the University of Catania, Italy and teaches Process Control and Complex Adaptive Systems. His scientific interests include linear systems, nonlinear dynamics, analysis and control of complex systems, and bio-inspired robotics.
Arturo Buscarino is currently a researcher in Automatic Control at the University of Catania, Italy. He is IEEE Senior Member. His scientific interests include nonlinear circuits and systems, chaos and synchronization, memristors, fuzzy logic, control systems, Cellular Nonlinear Networks, and plasma engineering.
Descriere
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.