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 time-varying 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
$(\mathcal{Q}, \mathcal{S},\mathcal{R})$
-
$\alpha $
-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
$(\mathcal{Q}, \mathcal{S},\mathcal{R})$
-
$\alpha $
-dissipative. Finally, the effectiveness of the proposed results is shown in numerical simulations.