Mathematical Methods in Robust Control of Discrete-Time Linear Stochastic Systems
Language: English
Published by Springer New York, 2009
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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US$ 208.82
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - In this monograph the authors develop a theory for the robust control of discrete-time stochastic systems, subjected to both independent random perturbations and to Markov chains. Such systems are widely used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. The theory is a continuation of the authors' work presented in their previous book entitled 'Mathematical Methods in Robust Control of Linear Stochastic Systems' published by Springer in 2006.Key features:- Provides a common unifying framework for discrete-time stochastic systems corrupted with both independent random perturbations and with Markovian jumps which are usually treated separately in the control literature;- Covers preliminary material on probability theory, independent random variables, conditional expectation and Markov chains;- Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations;- Leads the reader in a natural way to the original results through a systematic presentation;- Presents new theoretical resultswith detailed numerical examples.The 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.…
Seller Inventory # 9781441906298
- Title
- Mathematical Methods in Robust Control of Discrete-Time Linear Stochastic Systems
- Author
- Toader Morozan
- Publisher
- Springer New York
- Publication year
- 2009
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1441906290
- ISBN 13
- 9781441906298
- Item weight
- 675 grams
- Dimensions
- 242x164x30 mm
In this monograph the authors develop a theory for the robust control of discrete-time stochastic systems, subjected to both independent random perturbations and to Markov chains. Such systems are widely used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. The theory is a continuation of the authors’ work presented in their previous book entitled "Mathematical Methods in Robust Control of Linear Stochastic Systems" published by Springer in 2006.
Key features:
- Provides a common unifying framework for discrete-time stochastic systems corrupted with both independent random perturbations and with Markovian jumps which are usually treated separately in the control literature;
- Covers preliminary material on probability theory, independent random variables, conditional expectation and Markov chains;
- Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations;
- Leads the reader in a natural way to the original results through a systematic presentation;
- Presents new theoretical results with detailed numerical examples.
The 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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
In this monograph the authors develop a theory for the robust control of discrete-time stochastic systems, subjected to both independent random perturbations and to Markov chains. Such systems are widely used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. The theory is a continuation of the authors’ work presented in their previous book entitled "Mathematical Methods in Robust Control of Linear Stochastic Systems" published by Springer in 2006.
Key features:
- Provides a common unifying framework for discrete-time stochastic systems corrupted with both independent random perturbations and with Markovian jumps which are usually treated separately in the control literature
- Covers preliminary material on probability theory, independent random variables, conditional expectation and Markov chains
- Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations
- Leads the reader in a natural way to the original results through a systematic presentation
- Presents new theoretical results with detailed numerical examples
The 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.
"About the title" may belong to another edition of this title.
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