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Received:September 04, 2009Revised:September 04, 2009
基金项目:The National Natural Science Foundation of China,The Foundation for University Key Teachers from the Ministry of Education of China
Distributed model predictive control for multiagent systems with improved consistency
Shanbi WEI,Yi CHAI,Baocang DING
(chongqing university;Chongqi University)
This paper addresses an improved distributed model predictive control (DMPC) scheme for multiagent systems with an attempt to improving its consistency. The deviation between what an agent is actually doing and what its neighbors believe that agent is doing is penalized in the cost function of each agent. At each sampling instant the compatibility constraint of each agent is set tighter than the previous sampling instant. Like the traditional approach, the performance cost is utilized as the Lyapunov function to prove closed-looped stability. The closed-loop stability is guaranteed if the weight matrix for deviation in the cost function are sufficiently large. The proposed distributed control scheme is formulated as quadratic programming with quadratic constraints. A numerical example is given to illustrate the effectiveness of the proposed scheme.
Key words:  Distributed model predictive control (DMPC)  Multiagent systems  Compatibility constraint  Consistency