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Stochastic H2/H ∞ Control: A Nash Game Approach

Autor Weihai Zhang, Lihua Xie, Bor-Sen Chen
en Limba Engleză Hardback – 16 mai 2017
The H∞ control has been one of the important robust control approaches since the 1980s. This book extends the area to nonlinear stochastic H2/H∞ control, and studies more complex and practically useful mixed H2/H∞ controller synthesis rather than the pure H∞ control. Different from the commonly used convex optimization method, this book applies the Nash game approach to give necessary and sufficient conditions for the existence and uniqueness of the mixed H2/H∞ control. Researchers will benefit from our detailed exposition of the stochastic mixed H2/H∞ control theory, while practitioners can apply our efficient algorithms to address their practical problems.
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Specificații

ISBN-13: 9781466573642
ISBN-10: 1466573643
Pagini: 368
Ilustrații: 38
Dimensiuni: 160 x 234 x 25 mm
Greutate: 0.68 kg
Ediția:1
Editura: CRC Press

Cuprins

Mathematical Preliminaries. Linear Continuous-Time Stochastic H2 ∞ H1 Control. Linear Discrete-Time Stochastic H2  ∞ H1 Control. H2 ∞ H1 Control for Linear Discrete Time-Varying Stochastic Systems. Linear Markovian Jump Systems with Multiplicative Noise. Nonlinear Continuous-Time Stochastic H1 and H2 ∞ H1 Controls. Nonlinear Stochastic H1 and H2 ∞ H1 Filtering. Some Further Research Topics in Stochastic H2 ∞ H1 Control. Index.

Notă biografică

Weihai Zhang, Lihau Xie, Bor-Sen Chen

Descriere

The H∞ control has been one of the important robust control approaches since the 1980s. This book extends the area to nonlinear stochastic H2/H∞ control, and studies more complex and practically useful mixed H2/H∞ controller synthesis rather than the pure H∞ control. Different from the commonly used convex optimization method, this book applies the Nash game approach to give necessary and sufficient conditions for the existence and uniqueness of the mixed H2/H∞ control. Researchers will benefit from our detailed exposition of the stochastic mixed H2/H∞ control theory, while practitioners can apply our efficient algorithms to address their practical problems.