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Verlag: Springer New York, Springer New York Okt 2013, 2013
ISBN 10: 1461486629 ISBN 13: 9781461486626
Sprache: Englisch
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In den WarenkorbBuch. Zustand: Neu. Neuware -This second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems. More specifically, the new results presented are: A unified and abstract framework for Riccati type equations arising in the stochastic control Stability and control problems for systems perturbed by homogeneous Markov processes with infinite number of states MixedH2 / H¿control problem and numerical procedures Linear differential equations with positive evolution on ordered Banach spaces with applications for stochastic systems including both multiplicative white noise and Markovian jumps represented by a Markov chain with countable infinite set of states Kalman filtering for stochastic systems subject both to state dependent noise and Markovian jumps H¿reduced order filters for stochastic systemsThe book will appeal to graduate students, researchers in advanced control engineering, finance, mathematical systems theory, applied probability and stochastic processes, and numerical analysis.From Reviews of the First Edition:This book is concerned with robust control of stochastic systems. One of the main features is its coverage of jump Markovian systems. ¿ Overall, this book presents results taking into consideration both white noise and Markov chain perturbations. It is clearly written and should be useful for people working in applied mathematics and in control and systems theory. The references cited provide further reading sources.(George Yin, Mathematical Reviews, Issue 2007 m)This book considers linear time varying stochastic systems, subjected to white noise disturbances and system parameter Markovian jumping, in the context of optimal control ¿ robust stabilization, and disturbanceattenuation. ¿ The material presented in the book is organized in seven chapters. ¿ The book is very well written and organized. ¿ is a valuable reference for all researchers and graduate students in applied mathematics and control engineering interested in linear stochastic time varying control systems with Markovian parameter jumping and white noise disturbances.(Zoran Gajic, SIAM Review, Vol. 49 (3), 2007)Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 460 pp. Englisch.
Verlag: Springer New York, Springer New York Aug 2016, 2016
ISBN 10: 1493938703 ISBN 13: 9781493938704
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -This second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems. More specifically, the new results presented are: A unified and abstract framework for Riccati type equations arising in the stochastic control Stability and control problems for systems perturbed by homogeneous Markov processes with infinite number of states MixedH2 / H¿control problem and numerical procedures Linear differential equations with positive evolution on ordered Banach spaces with applications for stochastic systems including both multiplicative white noise and Markovian jumps represented by a Markov chain with countable infinite set of states Kalman filtering for stochastic systems subject both to state dependent noise and Markovian jumps H¿reduced order filters for stochastic systemsThe book will appeal to graduate students, researchers in advanced control engineering, finance, mathematical systems theory, applied probability and stochastic processes, and numerical analysis.From Reviews of the First Edition:This book is concerned with robust control of stochastic systems. One of the main features is its coverage of jump Markovian systems. ¿ Overall, this book presents results taking into consideration both white noise and Markov chain perturbations. It is clearly written and should be useful for people working in applied mathematics and in control and systems theory. The references cited provide further reading sources.(George Yin, Mathematical Reviews, Issue 2007 m)This book considers linear time varying stochastic systems, subjected to white noise disturbances and system parameter Markovian jumping, in the context of optimal control ¿ robust stabilization, and disturbanceattenuation. ¿ The material presented in the book is organized in seven chapters. ¿ The book is very well written and organized. ¿ is a valuable reference for all researchers and graduate students in applied mathematics and control engineering interested in linear stochastic time varying control systems with Markovian parameter jumping and white noise disturbances.(Zoran Gajic, SIAM Review, Vol. 49 (3), 2007)Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 460 pp. Englisch.
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Verlag: Springer New York, Springer New York, 2016
ISBN 10: 1493938703 ISBN 13: 9781493938704
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems. More specifically, the new results presented are: - A unified and abstract framework for Riccati type equations arising in the stochastic control- Stability and control problems for systems perturbed by homogeneous Markov processes with infinite number of states- Mixed H2 / H control problem and numerical procedures- Linear differential equations with positive evolution on ordered Banach spaces with applications for stochastic systems including both multiplicative white noise and Markovian jumps represented by a Markov chain with countable infinite set of states- Kalman filtering for stochastic systems subject both to state dependent noise and Markovian jumps- H reduced order filters for stochastic systems The book will appeal to graduate students, researchers in advanced control engineering, finance, mathematical systems theory, applied probability and stochastic processes, and numerical analysis.From Reviews of the First Edition: This book is concerned with robust control of stochastic systems. One of the main features is its coverage of jump Markovian systems. . Overall, this book presents results taking into consideration both white noise and Markov chain perturbations. It is clearly written and should be useful for people working in applied mathematics and in control and systems theory. The references cited provide further reading sources. (George Yin, Mathematical Reviews, Issue 2007 m)This book considers linear time varying stochastic systems, subjected to white noise disturbances and system parameter Markovian jumping, in the context of optimal control . robust stabilization, and disturbanceattenuation. . The material presented in the book is organized in seven chapters. . The book is very well written and organized. . is a valuable reference for all researchers and graduate students in applied mathematics and control engineering interested in linear stochastic time varying control systems with Markovian parameter jumping and white noise disturbances.(Zoran Gajic, SIAM Review, Vol. 49 (3), 2007).
Verlag: Springer New York, Springer New York, 2013
ISBN 10: 1461486629 ISBN 13: 9781461486626
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems. More specifically, the new results presented are: - A unified and abstract framework for Riccati type equations arising in the stochastic control- Stability and control problems for systems perturbed by homogeneous Markov processes with infinite number of states- Mixed H2 / H control problem and numerical procedures- Linear differential equations with positive evolution on ordered Banach spaces with applications for stochastic systems including both multiplicative white noise and Markovian jumps represented by a Markov chain with countable infinite set of states- Kalman filtering for stochastic systems subject both to state dependent noise and Markovian jumps- H reduced order filters for stochastic systems The book will appeal to graduate students, researchers in advanced control engineering, finance, mathematical systems theory, applied probability and stochastic processes, and numerical analysis.From Reviews of the First Edition: This book is concerned with robust control of stochastic systems. One of the main features is its coverage of jump Markovian systems. . Overall, this book presents results taking into consideration both white noise and Markov chain perturbations. It is clearly written and should be useful for people working in applied mathematics and in control and systems theory. The references cited provide further reading sources. (George Yin, Mathematical Reviews, Issue 2007 m)This book considers linear time varying stochastic systems, subjected to white noise disturbances and system parameter Markovian jumping, in the context of optimal control . robust stabilization, and disturbanceattenuation. . The material presented in the book is organized in seven chapters. . The book is very well written and organized. . is a valuable reference for all researchers and graduate students in applied mathematics and control engineering interested in linear stochastic time varying control systems with Markovian parameter jumping and white noise disturbances.(Zoran Gajic, SIAM Review, Vol. 49 (3), 2007).
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 346 | Sprache: Englisch | Produktart: Bücher.
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 346 | Sprache: Englisch | Produktart: Bücher.
Verlag: Springer New York, Springer US Nov 2010, 2010
ISBN 10: 1441921435 ISBN 13: 9781441921437
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Linear stochastic systems are successfully used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. This monograph presents a useful methodology for the control of such stochastic systems with a focus on robust stabilization in the mean square, linear quadratic control, the disturbance attenuation problem, and robust stabilization with respect to dynamic and parametric uncertainty. Systems with both multiplicative white noise and Markovian jumping are covered.Key Features:Covers the necessary pre-requisites from probability theory, stochastic processes, stochastic integrals and stochastic differential equationsIncludes detailed treatment of the fundamental properties of stochastic systems subjected both to multiplicative white noise and to jump Markovian perturbationsSystematic presentation leads the reader in a natural way to the original resultsNew theoretical results accompanied by detailed numerical examplesProposes new numerical algorithms to solve coupled matrix algebraic Riccati equations.The unique monograph is geared to researchers and graduate students in advanced control engineering, applied mathematics, mathematical systems theory and finance. It is also accessible to undergraduate students with a fundamental knowledge in the theory of stochastic systems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 324 pp. Englisch.
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Linear stochastic systems are successfully used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. This monograph presents a useful methodology for the control of such stochastic systems with a focus on robust stabilization in the mean square, linear quadratic control, the disturbance attenuation problem, and robust stabilization with respect to dynamic and parametric uncertainty. Systems with both multiplicative white noise and Markovian jumping are covered.Key Features:-Covers the necessary pre-requisites from probability theory, stochastic processes, stochastic integrals and stochastic differential equations-Includes detailed treatment of the fundamental properties of stochastic systems subjected both to multiplicative white noise and to jump Markovian perturbations-Systematic presentation leads the reader in a natural way to the original results-New theoretical results accompanied by detailed numerical examples-Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations.The unique monograph is geared to researchers and graduate students in advanced control engineering, applied mathematics, mathematical systems theory and finance. It is also accessible to undergraduate students with a fundamental knowledge in the theory of stochastic systems.
Verlag: Springer, 2006
Sprache: Englisch
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