🤖 AI Summary
This work addresses the challenge of enforcing both safety specifications and the requirement that certain events must be enabled in designated states—referred to as “mandatory events”—within discrete event systems. For the first time, mandatory events are formally incorporated into the supervisory control framework. The authors propose a novel formulation of the similarity control problem based on covariant-contravariant simulation relations, which unifies all constraints imposed by the specification. They establish necessary and sufficient conditions for the existence of a solution and present an efficient synthesis algorithm to construct the maximally permissive supervisor. This approach significantly enhances the modeling and control capabilities for complex behavioral constraints in discrete event systems.
📝 Abstract
In order to guarantee that a supervised system satisfies safety requirements of the specification, as well as requirements saying that in certain states certain events must be enabled, this paper introduces required events for discrete event systems and reconsiders the similarity control problem while taking all requirements from the specification into account. The notion of a covariant-contravariant simulation, which is finer than the conventional notion of simulation, is adopted to act as the behavioral relation of supervisory control theory. A necessary and sufficient condition for the solvability of this problem is established and a method for synthesizing a maximally permissive supervisor is provided.