샘플데이터 기반의 비선형시스템 제어기 설계: T-S 퍼지 시스템 접근법

This study considers a sampled-data stabilization problem for a nonlinear system, which was described using a Takagi-Sugeno (T-S) fuzzy system. In addition, a stabilization criterion was proposed by constructing Lyapunov functional, including looped-functional, and using a relaxation technique. The proposed Lyapunov functional utilized the sampling pattern and the relaxation technique exploited the information on the fuzzy membership functions. In addition, the relaxation technique generated additional slack variables, which enabled the analysis of the proposed stabilization criterion. Based on the Lyapunov functional and the relaxation technique, this study proposed the stabilization criterion in terms of linear matrix inequalities. The simulation results for the stabilization of a mass-spring system revealed the effectiveness of the proposed stabilization criterion.