引用本文:戴学丰.基于神经网络算法的实时DES监督控制[J].控制理论与应用,1997,14(5):708~711.[点击复制]
DAI Xuefeng.Supervisory Control of a Class of Real Time DES Based on Neural Networks Algorithm[J].Control Theory and Technology,1997,14(5):708~711.[点击复制]
基于神经网络算法的实时DES监督控制
Supervisory Control of a Class of Real Time DES Based on Neural Networks Algorithm
摘要点击 1234  全文点击 1121  投稿时间:1995-10-27  修订日期:1996-07-01
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DOI编号  
  1997,14(5):708-711
中文关键词  实时离散事件系统  实时最优控制  神经网络  优化算法  自动机  监督控制
英文关键词  real time discrete event systems  time optimal control  neural networks  optimization algorithm  automata  supervisory control
基金项目  
作者单位
戴学丰 齐齐哈尔轻工学院机电系.黑龙江齐齐哈尔 
中文摘要
      本文在包含状态转移时间离散事件系统(DES)的自动机模型基础上,引入神经网络优化算法用以确定表征闭环系统最大允许逻辑行为的语言K的一个某项指标最优的子集Kopt,并探讨了这种情况下用R-W理论设计监控DES的有关问题.
英文摘要
      In this paper we introduce the neural networks optimization algorithm to the discrete event systems (DES) with state transition times,which can be described by automata model, to determine language Kopt that not only is a subset of K representing closed-loop systems's behavioar in a minimally restrictive fashion but also makes a certain optimal performance index hold. And considered the issues related to the synthesis of supervisor using R-W theory.