A rule-based methodology for supervisory control of discrete event systems modelled as automation Petri nets

摘要

In this paper, a new rule-based methodology for the synthesis of Petri-net-based compiled supervisors for Discrete Event Systems (DESs) is proposed to solve the forbidden state problem. The methodology proposed ensures that the size of the supervisor to be synthesised is as small as possible and that the supervisor is nonblocking. The supervisor to be synthesised consists of a controlled Automation Petri Net (ARN) model of the system. In order to obtain the controlled APN model, the uncontrolled APN model, which represents the uncontrolled behaviour of the system and a set of token passing marking (TPM) rules are used. TPM rules are obtained by converting the forbidden state specifications into a set of related rules and they are implemented by using inhibitor and/or enabling arcs. APNs include the following extensions to the ordinary Petri net framework. sensor readings, as firing conditions at transitions, and actions, assigned to places. Ladder logic diagram code is used to implement the supervisor obtained. The applicability of this technique is demonstrated by considering a discrete manufacturing system.