Covering-based supervisory control of partially observed discrete event systems for state avoidance

In this work we present a new polynomial complexity approach to state avoidance for nondeterministic and partially observed discrete event systems. Our approach generates control based on a covering of the system state space that identifies overlapping sets of indistinguishable states. This approach is shown to be more permissive than existing state-feedback control techniques.