Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/88114
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Type: Journal article
Title: Robust finite-time H∞ control for nonlinear jump systems via neural networks
Other Titles: Robust finite-time H-infinity control for nonlinear jump systems via neural networks
Author: Luan, X.
Liu, F.
Shi, P.
Citation: Circuits, Systems and Signal Processing, 2010; 29(3):481-498
Publisher: Birkhauser
Issue Date: 2010
ISSN: 0278-081X
1531-5878
Statement of
Responsibility: 
Xiaoli Luan, Fei Liu, Peng Shi
Abstract: This paper presents a neural network-based robust finite-time H-infinity control design approach for a class of nonlinear Markov jump systems (MJSs). The system under consideration is subject to norm bounded parameter uncertainties and external disturbance. In the proposed framework, the nonlinearities are initially approximated by multilayer feedback neural networks. Subsequently, the neural networks undergo piecewise interpolation to generate a linear differential inclusion model. Then, based on the model, a robust finite-time state-feedback controller is designed such that the nonlinear MJS is finite-time bounded and finite-time stabilizable. The H-infinity control is specified to ensure the elimination of the approximation errors and external disturbances with a desired level. The controller gains can be derived by solving a set of linear matrix inequalities. Finally, simulation results are given to illustrate the effectiveness of the developed theoretic results
Rights: © Springer Science+Business Media, LLC 2010
DOI: 10.1007/s00034-010-9158-8
Appears in Collections:Aurora harvest 2
Electrical and Electronic Engineering publications

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