Robust Sampled-data Fuzzy Control for Nonlinear Systems and Its Applications: Free-Weight Matrix Method

In this paper, sampled-data control is proposed to stabilize the nonlinear system, which is expressed as a Takagi-Sugeno (T-S) fuzzy submodels. Based on suitable Lyapunov- Krasovskii functional (LKF) along with new weighted integral inequalities, the sufficient conditions are derived in terms of linear matrix inequalities, which ensure the exponential stability of the proposed closed loop T-S fuzzy system. The peculiarity of this paper is: as novel integral inequalities and LKF are proposed, less conservative results are provided when compared to existing results. Besides that, wind energy conversion systems, chaotic systems, and an inverted pendulum are validated with derived sufficient conditions. The corresponding simulation results show the merit of the proposed results over the existing works.