Improved stabilization results of fuzzy systems under variable sampling

This paper investigates the problem of stabilization for sampled-data fuzzy systems under variable sampling. By eliminating redundant variables, and combining a convex combination technique with a delay decomposition method to deal with nonlinear time-varying coefficients derived from the Jensen´s integral inequality, less conservative and less complex stabilization criteria are formulated as linear matrix inequalities (LMIs). An illustrative example is given to show the effectiveness and the improvement of the proposed method.