Robust coalitional model predictive control with negotiation of mutual interactions

Abstract

This article presents a robust coalitional model predictive control (MPC) approach where neighboring agents negotiate the bounds of their coupling variables. Also, the control variables of each agent are divided into a private part that is locally optimized, and a public part that is controlled by the corresponding neighbors. Under certain conditions, the agents communicate to update the bounds that determine the constraints on these private and public variables. Moreover, the mutual disturbances induced by coupling are considered using a tube-based approach, guaranteeing recursive feasibility and stability of the closed-loop system. The proposed method is tested on a simulated eight-input coupled tank benchmark to illustrate its benefits.