Robust T-S fuzzy-model-based nonfragile sampled-data control for cyber-physical systems with stochastic delay and cyber-attacks

This work addresses the nonfragile sampled-data control (SDC) of the Takagi-Sugeno (T-S) fuzzy model for cyber-physical systems (CPSs) subject to cyber-attacks (CAs). The sets of random variables satisfying the Bernoulli distribution are utilized to depict the probability of the data transmitted by the network being subjected to stochastic delay and CAs. Then, the information for the entire sampling interval (Formula presented.) to (Formula presented.) with a relation of the augmented state vectors is considered for designing the SDC of the T-S fuzzy systems (TSFSs). In this regard, the fractional delayed state looped functional (LF) approach is presented to handle the formulated Lyapunov-Krasovskii functional. Based on the LF method, new criteria are acquired to design SDC such that the proposed CPS is asymptotically stable in terms of linear matrix inequalities. It is worth noting that the proposed control strategy for the TSFSs guarantees stable performance while dealing with the attacks in the numerical section. Also, for the various attacking strengths of periodic and non-periodic nature, the TSFSs have been simulated to show the efficiency of the proposed control method. Additionally, three numerical models have been performed to validate the less conservatism and superiority of the derived results over the existing ones.