This paper addresses a distributed model predictive control (DMPC) scheme for multiagent systems with improving control\r\nperformance. In order to penalize the deviation of the computed state trajectory from the assumed state trajectory, the deviation\r\npunishment is involved in the local cost function of each agent. The closed-loop stability is guaranteed with a large weight\r\nfor deviation punishment. However, this large weight leads to much loss of control performance. Hence, the time-varying\r\ncompatibility constraints of each agent are designed to balance the closed-loop stability and the control performance, so that\r\nthe closed-loop stability is achieved with a small weight for the deviation punishment. A numerical example is given to illustrate\r\nthe effectiveness of the proposed scheme.
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