Gain-scheduling Distributed MPC for Polytopic Uncertain Systems subject to Actuator Saturation

In this paper, we present a gain-scheduling distributed model predictive control (MPC) algorithm for polytopic uncertain systems subject to actuator saturation. A large-scale system is decomposed into subsystems and sub-controllers are designed independently. An invariant set condition is provided and a min-max distributed MPC strategy is proposed based on the invariant set. The distributed MPC controller is determined by solving a linear matrix inequality (LMI) optimization problem. An iterative algorithm is provided to coordinate the sub-controllers. A numerical example is carried out to demonstrate the effectiveness of the proposed algorithm.