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Mathematical methods in robust control of linear stochastic systems

Author: Vasile Drăgan; Toader Morozan; Adrian Stoica
Publisher: New York : Springer, 2013.
Series: Mathematical concepts and methods in science and engineering, volume 50.
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Database:WorldCat
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Drăgan, Vasile.
Mathematical methods in robust control of linear stochastic systems
(DLC) 2006927804
(OCoLC)71747067
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Vasile Drăgan; Toader Morozan; Adrian Stoica
ISBN: 9781461486633 1461486637
OCLC Number: 861184347
Description: 1 online resource (xv, 442 pages) : illustrations.
Contents: Preliminaries to Probability Theory and Stochastic Differential Equations --
Linear Differential Equations with Positive Evolution on Ordered Banach Spaces --
Exponential Stability in Mean Square --
Structural Properties of Linear Stochastic Systems --
A Class of Nonlinear Differential Equations on an Ordered Linear Space of Symmetric Matrices with Applications to Riccati Differential Equations of Stochastic Control --
Linear Quadratic Optimization Problems for Linear Stochastic Systems --
Stochastic H₂ Optimal Control --
Stochastic Version of Bounded Real Lemma and Applications --
Robust Stabilization of Linear Stochastic Systems.
Series Title: Mathematical concepts and methods in science and engineering, volume 50.
Responsibility: Vasile Dragan, Toader Morozan, Adrian-Mihail Stoica.
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Mathematical Methods in Robust Control of Linear Stochastic Systems  Read more...

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From the reviews: "The subject of the book is related to the development of a theory of linear stochastic systems including both white noise and jump Markov perturbations, and to the development of Read more...

 
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schema:description"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 / Hcontrol 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 - Hreduced 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 disturbance attenuation. 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)"@en
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