On optimal attraction in discrete-event processes

The concept of attraction has been shown to play a basic role in the synthesis of supervisors for stabilizing discrete-event processes. In this paper we define and investigate optimal attraction optimal in the sense that the cost (or distance) of the convergence path is as small as possible with respect to some distance measure. We find conditions for the existence of supervisors achieving optimal attraction, and provide efficient algorithms for their synthesis.