Continuous-time Markov jump linear systems [Documento electrónico] / Oswaldo L. V. Costa, Marcelo D. Fragoso, Marcos G. Todorov
Language: eng.Country: Germany.Publication: Berlin, Heidelberg : Springer Berlin Heidelberg, 2013Description: XII, 288 p.ISBN: 978-3-642-34100-7.Series: Probability and Its ApplicationsSubject - Topical Name: Teoria de controlo | Processos de Markov Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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QA402.35.SPR FCT 82382 Analysis and design of nonlinear control systems | QA402.37.SPR FCT 81344 Optimal stochastic control, stochastic target problems, and backward SDE | QA402.37.SPR FCT 81466 Stochastic networked control systems, stabilization and optimization under information constraints | QA402.37.SPR FCT 82610 Continuous-time Markov jump linear systems | QA402.5. FCT 96362 Modeling discrete competitive facility location | QA402.5. FCT 96811 Modeling and optimization , theory and applications, MOPTA, Bethlehem, PA, USA, August 2014 selected contributions | QA402.5. FCT 97235 Generalized network improvement and packing problems |
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It has been widely recognized nowadays the importance of introducing mathematical models that take into account possible sudden changes in the dynamical behavior of high-integrity systems or a safety-critical system. Such systems can be found in aircraft control, nuclear power stations, robotic manipulator systems, integrated communication networks and large-scale flexible structures for space stations, and are inherently vulnerable to abrupt changes in their structures caused by component or interconnection failures. In this regard, a particularly interesting class of models is the so-called Markov jump linear systems (MJLS), which have been used in numerous applications including robotics, economics and wireless communication. Combining probability and operator theory, the present volume provides a unified and rigorous treatment of recent results in control theory of continuous-time MJLS. This unique approach is of great interest to experts working in the field of linear systems with Markovian jump parameters or in stochastic control. The volume focuses on one of the few cases of stochastic control problems with an actual explicit solution and offers material well-suited to coursework, introducing students to an interesting and active research area. The book is addressed to researchers working in control and signal processing engineering. Prerequisites include a solid background in classical linear control theory, basic familiarity with continuous-time Markov chains and probability theory, and some elementary knowledge of operator theory.
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