New results for sampled-data control of interval type-2 fuzzy nonlinear systems

This paper is devoted to the investigation of the interval type-2 (IT2) fuzzy sampled-data stabilization problem for the controlled plant subject to nonlinearities and parameter uncertainties. Some free-weighting matrices, slack matrices, and the bound information in membership functions are used to improve the stability analysis. Based on the Lyapunov-Krasovskii functional (LKF) theory, a new relaxed sufficient condition with fewer linear matrix inequality (LMI) constraints is derived. According to this criterion, the IT2 fuzzy sampled-data controller is devised to ensure the closed-loop system is asymptotically stable. Finally, three practical examples are provided to demonstrate the effectiveness and efficiency of the proposed design. Some comparisons show that the proposed algorithm is more simple and practical. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.