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Robust H∞ Performance of Discrete-time Neural Networks with Uncertainty and Time-varying Delay

M. Syed Ali, K. Meenakshi, R. Vadivel, and O. M. Kwon*
International Journal of Control, Automation, and Systems, vol. 16, no. 4, pp.1637-1647, 2018

Abstract : "In this paper, we are concerned with the robust H∞ problem for a class of discrete -time neural networks with uncertainties. Under a weak assumption on the activation functional, some novel summation inequality techniques and using a new Lyapunov-Krasovskii (L-K) functional, a delay-dependent condition guaranteeing the robust asymptotically stability of the concerned neural networks is obtained in terms of a Linear Matrix Inequality(LMI). It is shown that this stability condition is less conservative than some previous ones in the literature. The controller gains can be derived by solving a set of LMIs. Finally, two numerical examples result are given to illustrate the effectiveness of the developed theoretical results."

Keyword : H∞ control, linear matrix inequality, stability, time-varying delay.

 
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