Research on the stability of sliding mode control for ICPS under FDI attacks

To address the stability issues of nonlinear industrial cyber-physical system (ICPS) under false data injection (FDI) attacks and faults, this paper proposes a stability control strategy based on a T-S fuzzy sliding mode controller and a fuzzy variable proportional-integral observer. A smooth adaptive event-triggered mechanism is developed to reduce data transmission by adjusting its parameters according to output errors. The nonlinear system is linearised using a T-S fuzzy model, and the observer simultaneously estimates system states, attacks, and faults. An integral sliding surface and a fuzzy sliding mode controller with a boundary layer are designed to compensate for attacks and faults while suppressing chattering. By employing a Lyapunov–Krasovskii functional, the observer, controller, and event-triggering matrices are co-designed. MATLAB simulations of an industrial quadruple-tank system demonstrate that the proposed strategy maintains stability under simultaneous attacks and faults while effectively reducing the communication burden.