Fuzzy Sampled-Data Control for Synchronization of T–S Fuzzy Reaction–Diffusion Neural Networks With Additive Time-Varying Delays

This article focuses on the exponential synchronization problem of T-S fuzzy reaction-diffusion neural networks (RDNNs) with additive time-varying delays (ATVDs). Two control strategies, namely, time sampled-data and time-space are newly proposed. Compared some existing schemes, two schemes cannot only tolerate uncertainties but also save limited communication resources for considered systems. A new fuzzy-dependent adjustable matrix inequality technique is According to different plant controller rules, matrices introduced. In comparison traditional estimation techniques a determined constant matrix, approach more flexible. Then, by constructing suitable Lyapunov-Krasovskii functional (LKF) using approach, criteria derived RDNNs ATVDs. Meanwhile, desired gains obtained solving set linear inequalities (LMIs). end, simulations presented verify effectiveness superiority theoretical results.