Maximizing robustness of supervisors for partially observed discrete event systems

Abstract

We consider a robust supervisory control problem to synthesize a supervisor for the nominal plant model which maximizes robustness. Cury and Krogh have first addressed this problem by unnecessarily restricting the upper bound of the legal behavior. In our previous work, we have solved the problem without restricting the upper bound of the legal behavior when the specification is described by prefix-closed languages. In this paper, we extend our previous work to the partial (event) observation case. First, we synthesize a supervisor that maximizes robustness. This result shows that robustness can be optimized under partial observation, while permissiveness cannot be optimized in general. We next consider a special case where all the controllable events are observable. In this special case, we synthesize a maximally permissive supervisor for the nominal plant model which maximizes not only the robustness but also permissiveness for the maximal set of admissible plant variations.