Robust global exponential synchronization of uncertain chaotic delayed neural networks via dual-stage impulsive control

Authors:
Huaguang Zhang;Tiedong Ma;Guang-Bin Huang;Zhiliang Wang
Affiliations:
School of Information Science and Engineering, Northeastern University, Shenyang, China;School of Information Science and Engineering, Northeastern University, Shenyang, China;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Information Science and Engineering, Northeastern University, Shenyang, China
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Year:
2010

Citing 11
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Abstract

This paper is concerned with the robust exponential synchronization problem of a class of chaotic delayed neural networks with different parametric uncertainties. A novel impulsive control scheme (so-called dual-stage impulsive control) is proposed. Based on the theory of impulsive functional differential equations, a global exponential synchronization error bound together with some new sufficient conditions expressed in the form of linear matrix inequalities (LMIs) is derived in order to guarantee that the synchronization error dynamics can converge to a predetermined level. Furthermore, to estimate the stable region, a novel optimization control algorithm is established, which can deal with the minimum problem with two nonlinear terms coexisting in LMIs effectively. The idea and approach developed in this paper can provide a more practical framework for the synchronization of multiperturbation delayed chaotic systems. Simulation results finally demonstrate the effectiveness of the proposed method.