Robust stability criteria for discrete-time switched neural networks with various activation functions
作者： A. Arunkumar , R. Sakthivel , K. Mathiyalagan , S. Marshal Anthoni
DOI: 10.1016/J.AMC.2012.04.020
关键词: Control theory 、 Equilibrium point 、 Lyapunov function 、 Dwell time 、 Artificial neural network 、 Exponential stability 、 Discrete time and continuous time 、 Mathematics 、 Stability (probability) 、 Full state feedback
摘要: Abstract This paper is concerned with the problem of robust stabilization and H ∞ control for a class discrete-time switched neural networks various activation functions mixed time delays. By using average dwell approach together multiple Lyapunov function technique, we propose state feedback controller to guarantee that robustly exponentially stable disturbance attenuation level γ > 0 about its equilibrium point all admissible uncertainties. The obtained results are formulated in terms linear matrix inequalities (LMIs) which can be easily verified by MATLAB LMI toolbox. Finally, numerical examples simulation result given illustrate effectiveness applicability results.
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