Maharajan Chinnamuniyandi, Raja Ramachandran, Jinde Cao*, Grienggrai Rajchakit, and Xiaodi Li
International Journal of Control, Automation, and Systems, vol. 16, no. 2, pp.726-738, 2018

Abstract : "This paper mainly focuses on a novel H∞ control design to handle the global robust exponential stability problem for uncertain stochastic neutral-type neural networks (USNNNs) with mixed time-varying delays. Here the delays are assumed to be both discrete and distributed, which means that the lower and upper bounds can be derived. Firstly, we draw a control law for stabilized and stability of the neutral-type neural networks (NNNs). Secondly, by employing the Lyapunov-Krasovskii functional(LKF) theory, Jensen’s integral inequality, new required sufficient conditions for the global robust exponential stability of the given neural networks (NNs) are established in terms of delay-dependent linear matrix inequalities (LMIs), which can be easily checked in practice. The conditions obtained are expressed in terms of LMIs whose feasibility can be verified easily by MATLAB LMI control toolbox. Moreover, we have compared our work with previous one in the existing literature and showed that it reduces conservatism. Finally, one numerical example with their simulations is given to validate the effectiveness of our proposed theoretical results."

Keyword : "Global robust exponential stability, H∞ control, Linear matrix inequality, Lyapunov-Krasovskii functional, Mixed time-varying delays, Stochastic uncertain neutral-type neural networks."

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