Memory sampled-data control for interval type-2 fuzzy networked systems subjected to deception attacks via dynamic fragmentation approach

This study presents the fuzzy memory sampled -data controller (FMSDC) scheme for interval type -2 (IT -2) fuzzy networked systems subjected to deception attacks through a dynamic fragmentation approach. First, according to two partition coefficients 0 < mu(1), mu(2) < 1, a sampling interval is divided into four non -uniform intervals to take more advantage of dynamic information about the actual sampling pattern. Then, a novel integral inequality is introduced with a more accurate estimation for the sampling integrator terms involved in the fragmented states. Besides, an appropriate looped -type Lyapunov-Krasovskii functional (LTLKF) is constructed using sampling knowledge with transmission delay and fuzzy membership function information to minimize model conservatism. Next, based on the proposed integral inequality and constructed LTLKF combined with a switching strategy, some less conservative results in the form of linear matrix inequalities (LMIs) are derived to guarantee the stabilization of the addressed closed -loop system. Finally, we demonstrate the efficiency and feasibility of the suggested approach through numerical simulations and comparative results.