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Published in: Neural Computing and Applications 8/2020

16-08-2018 | Original Article

Non-fragile robust finite-time stabilization and \(H_{\infty }\) performance analysis for fractional-order delayed neural networks with discontinuous activations under the asynchronous switching

Authors: Xiao Peng, Huaiqin Wu

Published in: Neural Computing and Applications | Issue 8/2020

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Abstract

In this paper, the global non-fragile robust finite-time stabilization and \(H_{\infty }\) performance analysis are investigated for uncertain switched fractional-order neural networks with discontinuous activations, time delay and external disturbance under the asynchronous switching. Firstly, a new inequality, which is concerned with the fractional derivative of the variable upper limit integral for the nonsmooth integrable functional, is developed. Secondly, the non-fragile switched controller with two types of gain perturbations is designed. Under the Filippov fractional differential inclusion framework, the global non-fragile robust finite-time stabilization conditions are addressed in terms of linear matrix inequalities (LMIs) by applying nonsmooth analysis theory, inequality analysis technique, average dwell-time method and Lyapunov functional approach. In addition, the global non-fragile robust finite-time \(H_{\infty }\) performance analysis is performed, and the global non-fragile robust finite-time stabilization conditions with \(H_{\infty }\) disturbance attenuation level are also derived in the form of LMIs. Finally, two numerical examples are given to illustrate the feasibility of the proposed non-fragile switched controller and the validity of the theoretical results.

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Metadata
Title
Non-fragile robust finite-time stabilization and performance analysis for fractional-order delayed neural networks with discontinuous activations under the asynchronous switching
Authors
Xiao Peng
Huaiqin Wu
Publication date
16-08-2018
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 8/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3682-z

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