Event-Triggered Fuzzy Predictive Control of Nonlinear Cyber-Physical System Under Stochastic Communication Protocol Scheduling

The objective of this paper is to investigate an event-triggered output feedback model predictive control (MPC) approach for the nonlinear cyber-physical system (CPS) with a stochastic communication protocol (SCP) scheduling, which is approximated by an interval type-2 Takagi–Sugeno (IT2 T-S) fuzzy model. For the objective of enhancing network communication efficiency and relieving data collision caused by limited communication resource, an SCP protocol ruled by a Markov stochastic process is favourably utilized to govern the data scheduling of network. Based on an event-triggered output feedback control law, a mode-dependent IT2 fuzzy controller is formally designed, in which the feedback gain is optimized by solving an online constrained MPC optimization problem. By the utilization of defining the mean-square quadratic boundedness (MSQB) for confining the augmented system state into a robust invariant set, both the feasibility of controller and closed-loop stochastic stability are ensured and proved with the satisfaction of physical constraint in the mean-square sense. Finally, we validate the effectiveness of the proposed method by a numerical simulation example.