PSO-Algorithm-Assisted Attack-Compensated Control for 2-D Fuzzy Systems Under Cyber Attacks

The study investigates the problem of attack-compensated control for two-dimensional (2-D) fuzzy systems modeled by the Roesser framework, subject to the constraints of limited communication channels. A novel event-triggered stochastic protocol (ETSP) with nonhomogeneous sojourn probabilities is introduced to save communication resources. By randomly selecting a controller node at each time step to transmit signals, the protocol schedules communication between controllers and actuators, thereby reducing communication load. To address the injection of false data into control signals caused by network attacks, a compensation mechanism based on a sojourn-probability-based predictor is designed. Sufficient conditions are subsequently established, based on Lyapunov theory, to ensure the mean-square asymptotic stability of the closed-loop system while preserving the desired performance level. Finally, the particle swarm optimization (PSO) algorithm is employed to enhance the controller design, and a simulation example is provided to verify the effectiveness and applicability of the proposed method.