This book introduces a comprehensive methodology for adaptive control design of parabolic partial differential equations with unknown functional parameters, including reaction-convection-diffusion systems ubiquitous in chemical, thermal, biomedical, aerospace, and energy systems. Andrey Smyshlyaev and Miroslav Krstic develop explicit feedback laws that do not require real-time solution of Riccati or other algebraic operator-valued equations. The book emphasizes stabilization by boundary control and using boundary sensing for unstable PDE systems with an infinite relative degree. The book also presents a rich collection of methods for system identification of PDEs, methods that employ Lyapunov, passivity, observer-based, swapping-based, gradient, and least-squares tools and parameterizations, among others.
Including a wealth of stimulating ideas and providing the mathematical and control-systems background needed to follow the designs and proofs, the book will be of great use to students and researchers in mathematics, engineering, and physics. It also makes a valuable supplemental text for graduate courses on distributed parameter systems and adaptive control.
"The text is easy to read due to ubiquitous remarks, examples and explanations before and after the rigorous mathematical derivations. There are plenty of numerical simulations and figures that illustrate the control designs and compare them to each other. This book is recommended for everybody interested in control systems, system identification for PDEs, or just PDEs in general. From students to researchers, and from engineers to mathematicians everybody can find interesting new results in it."--Andras Balogh, Mathematical Reviews
"Unique and excellent, this book systematically and rigorously develops design and analysis tools and clearly explains technical concepts. As the first book to cover its topics, it significantly expands the scope of adaptive control knowledge. I strongly recommend this book as either a reference or an advanced textbook for researchers and graduate students who study and work in engineering and applied sciences."--Gang Tao, University of Virginia
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