Sampled-data stabilization for Takagi-Sugeno fuzzy systems using membership function deviations

This paper is concerned with sampled-data stabilization for Takagi-Sugeno (T-S) fuzzy systems by using the property of membership function deviations. A new lemma is presented to obtain an explicit estimate for the bounds of membership function deviations in sampled-data fuzzy control systems and to establish the quantitative relationship between the deviation bounds and the upper bound of sampling intervals. By using a piecewise Lyapunov-Krasovskii functional and a generalized Jensen integral inequality, a stability criterion is derived. Based on the stability criterion, a membership function deviation approach for designing a sampled-data fuzzy controller is proposed. Compared with some existing ones, the obtained results can reduce the conservativeness, which are confirmed by a numerical example.