Finite-time robust control of uncertain fractional-order Hopfield neural networks via sliding mode control

doi:10.1088/1674-1056/27/1/010202

Abstract The finite-time control of uncertain fractional-order Hopfield neural networks is investigated in this paper. A switched terminal sliding surface is proposed for a class of uncertain fractional-order Hopfield neural networks. Then a robust control law is designed to ensure the occurrence of the sliding motion for stabilization of the fractional-order Hopfield neural networks. Besides, for the unknown parameters of the fractional-order Hopfield neural networks, some estimations are made. Based on the fractional-order Lyapunov theory, the finite-time stability of the sliding surface to origin is proved well. Finally, a typical example of three-dimensional uncertain fractional-order Hopfield neural networks is employed to demonstrate the validity of the proposed method.

Keywords: fractional-order neural networks finite-time sliding mode control parameters estimation

Received: 05 May 2017
Revised: 25 September 2017
Accepted manuscript online:

PACS:

02.30.Yy

(Control theory)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 11371049 and 61772063) and the Fundamental Research Funds for the Central Universities, China (Grant No. 2016JBM070).

Corresponding Authors: Yongguang Yu
E-mail: ygyu@bjtu.edu.cn

Cite this article:

Yangui Xi(喜彦贵), Yongguang Yu(于永光), Shuo Zhang(张硕), Xudong Hai(海旭东) Finite-time robust control of uncertain fractional-order Hopfield neural networks via sliding mode control 2018 Chin. Phys. B 27 010202

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Finite-time robust control of uncertain fractional-order Hopfield neural networks via sliding mode control

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