Linear Robust Control
De (autor): Michael Green
Recent decades have witnessed enormous strides in the field of robust control of dynamical systems -- unfortunately, accounts of many of these developments are scattered in obscure research publications and accessible only to a small group of experts. In this highly regarded text for students and control engineers, the authors examine all of these advances, providing an in-depth examination of modern optimal and robust control.
After a brief introductory chapter, the text proceeds to examinations of multivariable frequency response design, signals and systems, and linear fractional transformations and their role in control systems. Subsequent chapters develop the control system synthesis theory, beginning with a concise treatment of the linear quadratic Gaussian problem and advancing to full-information H-infinity controller synthesis, the H-infinity filter, and the H-infinity generalized regulator problem. Concluding chapters examine model reduction by truncation, optimal model reduction, and the four-block problem. The text concludes with a pair of design case studies and helpful appendices. This treatment requires familiarity with linear algebra, matrix theory, linear differential equations, classical control theory, and linear systems theory.
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Recent decades have witnessed enormous strides in the field of robust control of dynamical systems -- unfortunately, accounts of many of these developments are scattered in obscure research publications and accessible only to a small group of experts. In this highly regarded text for students and control engineers, the authors examine all of these advances, providing an in-depth examination of modern optimal and robust control.
After a brief introductory chapter, the text proceeds to examinations of multivariable frequency response design, signals and systems, and linear fractional transformations and their role in control systems. Subsequent chapters develop the control system synthesis theory, beginning with a concise treatment of the linear quadratic Gaussian problem and advancing to full-information H-infinity controller synthesis, the H-infinity filter, and the H-infinity generalized regulator problem. Concluding chapters examine model reduction by truncation, optimal model reduction, and the four-block problem. The text concludes with a pair of design case studies and helpful appendices. This treatment requires familiarity with linear algebra, matrix theory, linear differential equations, classical control theory, and linear systems theory.
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