Robust state feedback model predictive control for constrained distributed large-scale systems with polytopic uncertainties

This paper investigates the robust state feedback model predictive control problem for the constrained distributed large-scale systems with polytopic uncertainties. It is assumed that all the states of the system are available and measurable. In distributed control, the goal is to improve thecontrol performance of the decentralized control by transmitting information among the subsystems. In this study, a set of locally distributed controllers is constructed for each subsystem by using min-max objective functions, which optimize the worst-case performance for a specified set of uncertainties. To reduce the computational complexity, we propose a new approach in which the designed algorithm is formulated in an optimization problem in terms of linear matrix inequality. The simulation results show that the proposed method performs well for the constrained large-scale interconnected systems, in the presence of parametric polytopic uncertainties.

کلیدواژه ها:

Interconnected system ، polytopic uncertainty ، distributed robust model predictive control ، linear matrix inequality ، min-max problem.