Observer-Based Dissipativity Control for T-S Fuzzy Neural Networks With Distributed Time-Varying Delays

An observer-based dissipativity control for Takagi-Sugeno (T-S) fuzzy neural networks with distributed timevarying delays is studied in this article. First, the network channel delays are modeled as a distributed delay with its kernel. To make full use of kernels of the distributed delay, a Lyapunov-Krasovskii functional (LKF) is established with the kernel of the distributed delay. It is noted that the novel LKF and delay-dependent reciprocally convex inequality plays an important role in dealing with global asymptotical stability and strict (Q, S, R)-a-dissipativity of the T-S fuzzy delayed model. Through the constructed LKF, a new set of less conservative linear matrix inequality (LMI) conditions is presented to obtain an observer-based controller for the T-S fuzzy delayed model. This proposed observer-based controller ensures that the state of the closed-loop system is globally asymptotically stable and strictly (Q, S, R)-a-dissipative. Finally, the effectiveness of the proposed results is shown in numerical simulations.

Automated summary

This article investigates the observer-based dissipativity control of Takagi-Sugeno (T-S) fuzzy neural networks with distributed time-varying delays. By establishing a new Lyapunov-Krasovskii functional and delay-dependent reciprocally convex inequality, the global asymptotical stability and strict (Q, S, R)-a-dissipativity are achieved. The effectiveness of the proposed results is demonstrated in numerical simulations.