Dynamic event-triggered networked predictive control for discrete-time NCSs under deception attacks

This paper investigates the dynamic event-triggered predictive control problem for discrete-time networked control systems under deception attacks. A new dynamic event-triggered scheme is proposed for discrete-time networked predictive control systems to reduce the data transmission. The feature of the dynamic event-triggered scheme is that the triggering threshold is adjusted dynamically. The Luenberger observer is provided to estimate the output measurements. The networked predictive control method is used to compensate for the time delay. Next, by using the piecewise linear model and the augmented model methods, sufficient conditions are established to guarantee the mean square asymptotic stability of the closed-loop systems, respectively. Finally, the effectiveness of the proposed approach is validated via a buck DC-DC converter system.