Robust Model Predictive Security Control for Networked Control Systems with Deception Attacks

This paper investigates the design of an output feedback model predictive controller for networked control systems subject to stochastic deception attacks. For the limited communication capability in actual network environments, an event-triggered mechanism is employed to reduce the consumption of network resources. A stochastic sequence that satisfies the Bernoulli distribution is utilized to describe the occurrence of deception attacks. Then, an event-triggered output feedback model predictive controller is constructed to generate the desired security performance. Based on the mean-square quadratic bounded theory, sufficient conditions are obtained to ensure the stochastic stability the security of established closed-loop systems. Finally, a numerical simulation is provided to show the effectiveness of the designed algorithm.