H∞ state estimation for T-S fuzzy neural networks with mixed time delays using secondary delay partitioning method

This paper adopts a secondary delay partitioning method to analyze the H-infinity state estimation problem of T-S fuzzy neural networks with discrete and distributed delays. The delay interval is first divided into two parts, and each part is divided into several unequal subintervals. The two parts are connected by a term of the newly augmented Lyapunov-Krasovskii functional which is a double integral term with variable upper and lower limits of the integral. Using a new integral inequality which gives a sharper upper bound than Jensen's inequality and combining with extended reciprocal convex combination, novel delay-dependent criteria are obtained to guarantee that the zero solution of the error system is globally asymptotically stable with H-infinity performance index gamma. A numerical example is used to illustrate the effectiveness of the proposed method.