Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode |
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E-Books | Biblioteca da FCTUNL Online | Não Ficção | QA402.3.SPR FCT 81122 (Browse shelf) | 1 | Available |
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QA402.3.SPR FCT 80851 Stochastic control in discrete and continuous time | QA402.3.SPR FCT 81023 Robust output LQ optimal control via integral sliding modes | QA402.3.SPR FCT 81104 Bilinear control systems | QA402.3.SPR FCT 81122 Mathematical methods in robust control of discrete-time linear stochastic systems | QA402.3.SPR FCT 81184 Analysis and design of descriptor linear systems | QA402.3.SPR FCT 81314 Semi-discretization for time-delay systems | QA402.3.SPR FCT 81542 Mathematical methods in robust control of linear stochastic systems |
Colocação: Online
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.
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