Disturbance observer-based adaptive event-triggered MPC for a class of nonlinear systems

In this paper, a disturbance observer-based adaptive event-triggered model predictive control (DAEMPC) method is proposed for a class of nonlinear systems with constraints and bounded disturbances. First, a disturbance observer is employed to actively compensate for disturbances. Leveraging the space decomposition technique, the disturbances are divided into the matched parts and the remaining unmatched parts. The matched disturbances are compensated using the pre-designed disturbance observer. To address the effects caused by the remaining unmatched disturbances, a bounded controller and an optimal controller with an adaptive event-triggered mechanism are respectively designed based on whether the system state resides within the stable region. The larger terminal stability estimation set is calculated based on the bounded controller. Furthermore, rigorous theoretical analysis is performed to prevent Zeno behavior. Finally, the simulation results for two numerical examples verify the effectiveness of the proposed algorithm.