Distributed model predictive control for polytopic uncertain systems subject to actuator saturation

• A robust distributed MPC algorithm for polytopic uncertain systems was developed.
• Less conservative results were obtained for system subject to actuator saturation.
• Computational complexity and time cost were reduced using distributed control.
• Trade-off between computational time and performance was studied.

In this paper, we present a distributed model predictive control (MPC) algorithm for polytopic uncertain systems subject to actuator saturation. The global system is decomposed into several subsystems. A set invariance condition for polytopic uncertain system with input saturation is identified and a min–max distributed MPC strategy is proposed. The distributed MPC controller is designed by solving a linear matrix inequalities (LMIs) optimization problem. An iterative algorithm is developed for making coordination among subsystems. Case studies are carried out to illustrate the effectiveness of the proposed algorithm.