Model Predictive Control for T-S Fuzzy Systems Under Event-Trigger Mechanism

This paper is concerned with the model predictive control (MPC) for Takagi-Sugeno (T-S) fuzzy systems under the event-triggered mechanism. First, in order to make a rational and effective utilization of the communication resources, the event-triggered mechanism is employed in the network from the controller to the actuator. Second, a “min-max” optimization is put forward to dealing with the MPC problem for systems in the context of T-S fuzzy nonlinearities, and an online auxiliary optimization problem is constructed to obtain sub-optimal feedback gains. Third, by fully taking the influence of the event-triggered mechanism and the T-S fuzzy nonlinearities into consideration, some sufficient conditions are provided to guarantee the input-to-state stability (ISS) for the underlying system. Finally, a numerical example is given to illustrate the effectiveness of the robust MPC-based controller for the closed-loop system under the event-triggered mechanism.

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