Title: Extended state estimator design method for neutral-type neural networks with time-varying delays
Authors: Magdi Sadek Mahmoud
Addresses: Systems Engineering Department, King Fahd University of Petroleum and Minerals, P.O. Box 985, Dhahran 31261, Saudi Arabia
Abstract: The problem of designing a state estimator having a global exponential convergence for a class of delayed neural networks of neutral-type is investigated in this paper. The time-delay pattern is a bounded differentiable time-varying function. The activation functions are globally Lipschitz. A linear estimator of Luenberger-type is developed and by properly constructing a new Lyapunov-Krasovskii functional coupled with the integral inequality, the global exponential stability conditions of the error system are derived. The unknown gain matrix is determined by solving a delay-dependent linear matrix inequality. The developed results are shown to be less conservative than previous published ones in the literature, which is illustrated by a representative numerical example.
Keywords: delayed neural networks; DNNs; state estimation; global exponential stability; interval time-varying delay; LMI; linear matrix inequality.
International Journal of Systems, Control and Communications, 2012 Vol.4 No.1/2, pp.1 - 19
Available online: 20 Mar 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article