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中文摘要：
针对知识化制造系统中的动态调度问题，结合知识化制造单元的高智能特征，提出了B-Q学习算法．并基于该算法构建了一种自适应调度控制策略．针对知识化制造系统运行过程中系统状态空间较大的特点，通过提取系统状态特征，对系统状态进行合理聚类，有效地降低了系统状态空间的复杂性．根据系统当前所处的瞬时状态．选取不同的调度规则对缓冲区中工件进行有效调度．仿真结果验证了所提出调度控制策略的有效性．
英文摘要：
Aiming to the problem of dynamic scheduling in knowledgeable manufacturing system, the B-Q learning algorithm is proposed by combining the high intelligent characteristic of knowledgeable manufacturing cell, and a kind of adaptive scheduling control strategy is presented based on this algorithm. In view of the characteristic of a large scale state space during KMS running, through the extraction of state feature and reasonable state clustering, the complexity of system state space is reduced effectively. According to current system transient state, different dispatch rules of scheduling the jobs are selected, and thus the effective scheduling can be obtained for the orders in buffer. Simulation results show the effectiveness of the scheduling control strategy.
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