Secure Multiplicative Sampled-Data Control for T-S Fuzzy-Based Cyber-Physical Systems Subject to Deception Attacks

This work addresses the secure control problem of T-S fuzzy-based cyber-physical systems (TSFCPSs) under randomly occurring deception attacks (RODAs). Random variables following the Bernoulli distribution are used to model the probability of false data injection by malicious adversaries. A novel memory-based sampled-data control (MSDC) scheme is developed to counter RODAs and multiplicative control gain uncertainties (MCGUs), both of which follow the Bernoulli distribution. The MSDC design for the TSFCPSs considers information over the entire sampling interval, \(t_k\) $t_k$ to \(t_{k+1}\) $t_{k+1}$ , and accounts for signal transmission delays in relation to the augmented state vectors. The looped functional (LF) approach is employed to address the formulated Lyapunov-Krasovskii functional. New stabilization criteria, based on the LF method, are derived in terms of linear matrix inequalities to ensure the proposed TSFCPSs are asymptotically stable despite RODAs and MCGUs. An illustrative example of a power system with a doubly-fed induction generator-based wind turbine demonstrates the effectiveness and advantages of the proposed MSDC in achieving the desired performance.