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https://hdl.handle.net/2440/78728
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Type: | Journal article |
Title: | Neural-network-based finite-time H∞ control for extended Markov jump nonlinear systems |
Other Titles: | Neural-network-based finite-time H infinity control for extended Markov jump nonlinear systems |
Author: | Luan, X. Liu, F. Shi, P. |
Citation: | International Journal of Adaptive Control and Signal Processing, 2010; 24(7):554-567 |
Publisher: | John Wiley & Sons Ltd |
Issue Date: | 2010 |
ISSN: | 0890-6327 1099-1115 |
Statement of Responsibility: | Xiaoli Luan, Fei Liu and Peng Shi |
Abstract: | <jats:title>Abstract</jats:title><jats:p>This paper presents a neural‐network‐based finite‐time <jats:italic>H</jats:italic><jats:sub>∞</jats:sub> control design technique for a class of extended Markov jump nonlinear systems. The considered stochastic character is described by a Markov process, but with only partially known transition jump rates. The sufficient conditions for the existence of the desired controller are derived in terms of linear matrix inequalities such that the closed‐loop system trajectory stays within a prescribed bound in a fixed time interval and has a guaranteed <jats:italic>H</jats:italic><jats:sub>∞</jats:sub> noise attenuation performance for all admissible uncertainties and approximation errors of the neural networks. A numerical example is used to illustrate the effectiveness of the developed theoretic results. Copyright © 2009 John Wiley & Sons, Ltd.</jats:p> |
Keywords: | Markov jump systems nonlinearities finite-time stabilization H∞ control transition probabilities neural networks |
Rights: | Copyright © 2009 John Wiley & Sons, Ltd. |
DOI: | 10.1002/acs.1143 |
Published version: | http://dx.doi.org/10.1002/acs.1143 |
Appears in Collections: | Aurora harvest Electrical and Electronic Engineering publications |
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