Intelligent Supervisory Control Through Discrete Event System Identification

本课题研究了用于监督式智能控制器综合的离散事件系统(DES)动态辨识问题。这样的系统通过将其建模为一系列逻辑事件来表示复杂工厂的行为，例如计算机磁盘控制系统。监督控制器是一个控制混杂系统的离散事件系统。本项目对获取DES对象模型的有效方法进行了研究。使用的具体技术包括使用归纳推理过程定义观察事件的状态空间分区的优化设计，强调相对较低的计算负担和降低的样本复杂性。

This research project deals with the identification of discrete event system (DES) dynamics for synthesis of supervisory intelligent controllers. Such systems represent a complex plant's behavior by modeling it as a sequence of logical events, e.g., a computer disk control system. The supervisory controller is a DES controlling a hybrid system. Investigation of efficient methods for obtaining DES plant models are carried out in this project. Specific techniques used include the optimal designs of state space partitions defining the observed events using inductive inference procedures, with an emphasis on relatively low computational burden and reduced sample complexity.*** //