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On-line identification of language measure parameters for discrete-event supervisory control

机译:用于离散事件监督控制的语言度量参数的在线识别

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The discrete-event dynamic behavior of physical plants is often represented by regular languages that can be realized as deterministic finite state automata (DFSA). The concept and construction of signed real measures of regular languages have been recently reported in literature. Major applications of the language measure are: quantitative evaluation of the discrete-event dynamic behavior of unsupervised and supervised plants; and analysis and synthesis of optimal supervisory control algorithms in the discrete-event setting. This paper formulates and experimentally validates an on-line procedure for identification of the language measure parameters based on a DFSA model of the physical plant. The recursive algorithm of this identification procedure relies on observed simulation and/or experimental data. Efficacy of the parameter identification procedure is demonstrated on the test bed of a mobile robotic system, whose dynamic behavior is modelled as a DFSA for discrete-event supervisory control.
机译:物理植物的离散事件动态行为通常由可实现为确定性有限状态自动机(DFSA)的常规语言表示。最近在文献中已经报道了常规语言的已签名真实度量的概念和构造。语言度量的主要应用是:对无监督和受监督工厂的离散事件动态行为进行定量评估;离散事件环境下最优监督控制算法的分析与综合。本文提出并通过实验验证了基于物理工厂的DFSA模型的语言度量参数识别的在线过程。该识别过程的递归算法依赖于观察到的模拟和/或实验数据。在移动机器人系统的测试平台上演示了参数识别过程的有效性,该系统的动态行为被建模为用于离散事件监督控制的DFSA。

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