Simplifying supervisory controllers of automated manufacturing systems via Petri net modeling and multiset analysis

This paper presents new results on structural simplification of a supervisor in a Petri net framework. Supervisor simplification is essential to the efficient and effective functionality of an automated manufacturing system. This work is motivated by the fact that some properties have not been thoroughly explored in the prior supervisor design and simplification studies. If a supervisor is structurally simpler than and behaviorally analogous to another, it is viewed to be better irrespective of its composition. In the semantics of multiset, this work defines the concept of a minimum covering set and derives a necessary and sufficient condition for the existence of a simplest supervisor. Next, it develops an algorithm to compute the optimal supervisor in sense of structural simplicity. An example is provided to illustrate the proposed algorithm. Additionally, a discussion is conducted to distinguish the proposed one from others in literature.