An LMI approach for global robust dissipativity analysis of T–S fuzzy neural networks with interval time-varying delays

Takagi–Sugeno (T–S) fuzzy models are often used to represent complex nonlinear systems by means of fuzzy sets and fuzzy reasoning applied to a set of linear sub-models. In this paper, the global robust dissipativity of T–S fuzzy neural networks with interval time-varying delays are investigated. By constructing a proper Lyapunov–Krasovskii functional and using linear matrix inequality (LMI) technique, delay-dependent criteria for checking the global dissipativity and global exponential dissipativity of fuzzy neural networks have been derived in terms of LMI, which can be solved numerically using LMI toolbox in MATLAB. Finally, numerical examples are given to illustrate the effectiveness of the theoretical results.