Abstract
For the control of a class of large-scale systems, which consists of many individual subsystems, the distributed contort framework is more suitable because of its good flexibility and error tolerant, despite the fact that its performance is not as good as that of centralized control. How to improve the performance of the entire system and, at the same time,maintain the flexibility and error tolerance characterises under the distributed framework is an important problem. In this paper, a novel distributed model predictive control(DMPC) is proposed, which enlarges the coordinate degree of DMPC through adding a quasi-function of the impact of control input to its downstream subsystems to the performance index of each subsystem-based model predictive control(MPC). Then, the performance of the entire system is improved with unchanged network connectivity. In addition, a design method with this coordination strategy and inputs constraints is provided, which guarantees the recursive feasiblity of the designed DMPC and asymptotic stablility of the closed-loop system.
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