Stochastic Switching Systems [electronic resource] :Analysis and Design / by El-Kébir Boukas.
by Boukas, El-Kébir [author.]; SpringerLink (Online service).
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QA401-425 Approximation Theory | QA241-247.5 Complex Numbers from A to... Z | QA639.5-640.7 Selected Topics in Convex Geometry | Stochastic Switching Systems | QC120-168.85 Continuum Mechanics using Mathematica® | TA703-705.4 Neural Networks and Sea Time Series | QA172-172.4 The Congruences of a Finite Lattice |
Stability Problem -- Stabilization Problem -- ?? Control Problem -- Filtering Problem -- Singular Stochastic Switching Systems.
Stochastic switching systems represent an interesting class, which can be used to model a variety of systems having abrupt random changes in their dynamics. Such systems may be found in the fields of manufacturing, communications, aerospace, power, and economics. This work presents stochastic switching systems and provides up-to-date methods and techniques for the analysis and design of various control systems with or without uncertainties. An introductory chapter highlights basic concepts and practical models, which are then used to solve more advanced problems throughout the book. Included are many numerical examples as well as LMI analysis methods and design approaches to supplement the developed results. Specific topics covered include: * The stochastic stability problem and its robustness. * The stabilization problem; different controllers such as the state feedback, output feedback, and observer-based output feedback are designed for nominal and uncertain systems using LMI conditions. * Systems with external disturbances; different approaches are developed to reject the external disturbances. * The filtering problem for the class of systems with Markovian jump parameters; Kalman and H-infinity filtering problems are treated and LMI conditions are developed to synthesize the gains of these filters. * Systems with singular Markovian jump parameters. Stochastic Switching Systems may be used as a supplementary textbook for graduate-level engineering courses, or as a reference for control engineers, graduate students, and researchers in systems and control. Prerequisites include elementary courses in matrix theory, probability, optimization techniques, and control systems theory.
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