Synthesis of distributed MPC with structured uncertainties

Abstract

In this paper, a distributed model predictive control (MPC) approach is presented for a class of linear systems with structured time-varying uncertainties. A global system is represented as several small dimensional subsystems. A set of distributed sate feedback laws are designed at each time instant to ensure the robust stability of the closed-loop system with respect to the structured uncertainties. Considering the influences of neighbor subsystems, the robust distributed MPC controller design problem is formulated into solving a minimizing optimization problem of performance index. The design of robust distributed MPC controller is then cast into solving a linear matrix inequality (LMI) optimization problem. A global performance is achieved by using an iterative algorithm. Finally, the proposed distributed MPC algorithm is demonstrated by a simulation example.