LAUSR

This paper describes a state-based approach for supervisor synthesis of discrete-event systems under partial observation, based on predicates and predicate transformers. We focus on the normality property and provide an iterative algorithm for state-based normality synthesis. A condition is provided to simplify the algorithm. To bridge the gap between language-based normality synthesis and state-based normality synthesis, we prove that their synthesis results are mutually consistent. This paper also aims to build a useful foundation for non-blocking supervisor synthesis of partially-observed state tree structures, which is essentially a state-based approach. The proposed approach is illustrated with a Guideway example taken from the literature.