Periodic Model Predictive Control for Uncertain Norm-Bounded Systems With AETSCP Scheduling and Hybrid Attacks

This article examines the issue of periodic model predictive control (PMPC) output feedback-based for a class of uncertain norm-bounded systems over digital communication network. A novel adaptive event-triggered stochastic communication protocol (AETSCP) scheduling is devised to alleviate the communication burden of the shared network. Meanwhile, the security issue of hybrid attacks, involving Denial of Service (DoS) attacks and deception attacks on the system, is considered. The quadratic boundedness (QB) technique is utilized to represent the closed-loop stability of the related networked control systems (NCSs). In addition, the periodic model predictive controller, which allows system states to temporarily leave the ellipsoidal set but return to the original ellipsoidal set at finite time steps, is synthesized based on the dynamic output feedback. Subsequently, sufficient conditions are provided to ensure that the augmented states gradually converge and the estimation error bound becomes tighter. It is demonstrated that the proposed algorithm enlarges the attraction region and yields better control performance. Finally, the validity of our proposed algorithm is confirmed by a simulation example.