Model Predictive Control for Interval Type-2 T-S Fuzzy Systems Under New Dynamic Event-Triggered Mechanism

In this paper, we focus on dynamic event-triggered model predictive control (MPC) problem for interval type-2 Takagi-Sugeno (IT2 T-S) fuzzy systems with hard constraints on the state. A dynamic event-triggered mechanism (DETM) with two adjusting variables is devised to reduce data transmission burden. The MPC problem is formulated as a "min-max" problem over the infinite horizon. Our purpose is to find a series of desired sub-controllers in terms of MPC such that the underlying IT2 T-S fuzzy system is asymptotically stable. By taking the T-S fuzzy nonlinearities and the DETM into consideration, we give the design method of the controller through an online auxiliary optimization problem with several constraint conditions. A simulation example is used to demonstrate the effectiveness and the validity of the proposed methods.