论文部分内容阅读
针对Petri网控制问题中不可控子网的状态空间指数级增长导致的计算复杂性难题,提出了控制目标(线性约束)等价的网结构压缩算法:(1)将不可控子网部分区域压缩为单个库所;(2)并将原网上的线性约束等价转换为新网的新线性约束.反复迭代该算法,可以有效地压缩原不可控子网,从而指数级地减小不可控子网的状态空间,有效地降低监控问题的计算复杂性,甚至当不可控子网为状态机时,该方法能够彻底解决上述计算复杂性难题,获得高效最优的Petri网监控器,并用一个物料运输系统演示了该方法.
Aiming at the computational complexity caused by the exponential growth of the state space of uncontrollable subnets in the Petri net control problem, a network structure compression algorithm with control target (linear constraint) equivalent is proposed. (1) (2) The linear constraints on the original network are transformed into the new linear constraints of the new network iteratively iteratively, which can effectively compress the original uncontrollable sub-networks and exponentially reduce the uncontrollable sub-networks The state space of the network effectively reduces the computational complexity of the monitoring problem. Even when the uncontrollable subnet is a state machine, this method can completely solve the above computational complexity problem and obtain a highly effective and optimal Petri net monitor. With a material The transport system demonstrates this method.