Robust Control Of Jump Linear Stochastic Systems


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Robust Control of Jump Linear Stochastic Systems


Robust Control of Jump Linear Stochastic Systems

Author: Vasile Drăgan

language: en

Publisher: Springer Nature

Release Date: 2025-07-18


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This monograph concentrates on the theory of robust control of linear impulsive stochastic systems and stochastic systems with jumps. It discusses theoretical points concerned with impulsive stochastic systems including optimal control, robust stabilization, and H2- and Hinfinity-type results. Considering the major role played by the impulsive Lyapunov and impulsive Riccati equations in these problems, the book presents a thorough treatment of these equations in a general framework. It also presents various applications to sampled-data control. Robust Control of Jump Linear Stochastic Systems is a self-contained and clearly structured presentation of up-to-date research in this area, relevant to researchers in control theory and to non-specialists who are interested in the theory of robust control of linear impulsive stochastic systems. Theoretical and applied mathematicians, research engineers, and graduate students in the aforementioned fields will also find value in this book.

Mathematical Methods in Robust Control of Linear Stochastic Systems


Mathematical Methods in Robust Control of Linear Stochastic Systems

Author: Vasile Dragan

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-10-04


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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 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)

Discrete-Time Markov Jump Linear Systems


Discrete-Time Markov Jump Linear Systems

Author: O.L.V. Costa

language: en

Publisher: Springer Science & Business Media

Release Date: 2006-03-30


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Safety critical and high-integrity systems, such as industrial plants and economic systems can be subject to abrupt changes - for instance due to component or interconnection failure, and sudden environment changes etc. Combining probability and operator theory, Discrete-Time Markov Jump Linear Systems provides a unified and rigorous treatment of recent results for the control theory of discrete jump linear systems, which are used in these areas of application. The book is designed for experts in linear systems with Markov jump parameters, but is also of interest for specialists in stochastic control since it presents stochastic control problems for which an explicit solution is possible - making the book suitable for course use. From the reviews: "This text is very well written...it may prove valuable to those who work in the area, are at home with its mathematics, and are interested in stability of linear systems, optimal control, and filtering." Journal of the American Statistical Association, December 2005