Control of Discrete-Time Descriptor Systems takes an anisotropy-based approach to the explanation of random input disturbance with an information-theoretic representation. It describes the random input signal more precisely, and the anisotropic norm minimization included in the book enables readers to tune their controllers better through the mathematical methods provided. The book contains numerous examples of practical applications of descriptor systems in various fields, from robotics to economics, and presents an information-theoretic approach to the mathematical description of coloured…mehr
Control of Discrete-Time Descriptor Systems takes an anisotropy-based approach to the explanation of random input disturbance with an information-theoretic representation. It describes the random input signal more precisely, and the anisotropic norm minimization included in the book enables readers to tune their controllers better through the mathematical methods provided. The book contains numerous examples of practical applications of descriptor systems in various fields, from robotics to economics, and presents an information-theoretic approach to the mathematical description of coloured noise. Anisotropy-based analysis and design for descriptor systems is supplied along with proofs of basic statements, which help readers to understand the algorithms proposed, and to undertake their own numerical simulations. This book serves as a source of ideas for academic researchers and postgraduate students working in the control of discrete-time systems. The control design procedures outlined are numerically effective and easily implementable in MATLAB®
Alexey A. Belov received the Ph.D. degree in System Analysis, Data Processing and Control from the V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences (ICS RAS), Moscow, Russia, in 2011. He is currently a Senior Researcher of the Department of Control Systems and Informatics at ITMO University and Senior Researcher of Laboratory of Dynamics of Control Systems at ICS RAS. His research interests include stability and control of descriptor systems, anisotropy-based and robust control of linear systems. Olga G. Andrianova received Ph.D. degree in System Analysis, Data Processing and Control from the V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences (ICS RAS), Moscow, Russia, in 2015. She is currently a Senior Researcher of the Laboratory of Dynamics of Control Systems, ICS RAS, and an Associate Professor of the School of Applied Mathematics, MIEM HSE. Her scientific interests are focused on anisotropy-based control of descriptor systems and robust control of discrete-time linear systems.¿ Alexander Kurdyukov received the Ph.D degree in System Analysis, Data Processing and Control from the V.A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences (ICS RAS), Moscow, Russia, in 1980 and Doctor Degree in System Analysis, Data Processing and Control from the V.A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences (RAS), Moscow, Russia, in 2001. He is currently a Head of Laboratory of Dynamics of Control Systems in ICS RAS. He is a specialist in adaptive, robust and stochastic robust control. He published more than 100 published works including 7 monographs (in Russian).
Inhaltsangabe
Practical Application of Descriptor Systems.- Basics of Discrete-time Descriptor Systems Theory.- Anisotropy-based Analysis of LDTI Descriptor Systems.- Optimal Control.- Suboptimal Control.- Anisotropy-based Analysis for LDTI Descriptor Systems with Nonzero-Mean Input Signals.- Robust Anisotropy-based Control.
Practical Application of Descriptor Systems.- Basics of Discrete-time Descriptor Systems Theory.- Anisotropy-based Analysis of LDTI Descriptor Systems.- Optimal Control.- Suboptimal Control.- Anisotropy-based Analysis for LDTI Descriptor Systems with Nonzero-Mean Input Signals.- Robust Anisotropy-based Control.
Rezensionen
"The book presents recent results on the anisotropy based optimal control of discrete time descriptor systems. It will be of high value to all researchers interested in the field and its future developments." (Lazaros Moysis, zbMATH 1391.93001, 2018)
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