Event-triggered distributed robust model predictive control for a class of nonlinear interconnected systems

Abstract

In this work, we develop an event-triggered distributed robust model predictive control algorithm to stabilize the origin of a class of interconnected systems with nonlinear coupling terms and additive bounded disturbances. Each subsystem is assumed to be able to exchange information with its neighboring subsystems. The transmitted information between neighbors is used to estimate their future behaviors. Then, a robust distributed model predictive control algorithm for each subsystem is developed by integrating the estimations of its neighbors and each subsystem executes a local model predictive control law after solving its optimization problem. Furthermore, a distributed event-triggered mechanism is designed to trigger a series of asynchronous computations of the optimization problems, which achieves a trade-off between communication resource usage and control performance. Theoretical conditions on ensuring feasibility and closed-loop stability are provided. Finally, a practical example of the multi-machine power system with governor controllers is provided to show the effectiveness of the proposed algorithm.