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

ABSTRACT 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.