Hierarchical Supervisory Control under Partial Observation: Normality

TL;DR

This paper investigates conditions for preserving normality in hierarchical supervisory control of discrete-event systems under partial observation, introducing modified observation consistency and analyzing its computational complexity.

Contribution

It defines modified observation consistency to ensure supremal normal sublanguages coincide across levels and discusses its computational properties and practical verification methods.

Findings

Modified observation consistency guarantees supremal normal sublanguage equivalence.

Verification of (modified) observation consistency is PSPACE-hard for finite automata.

Decidability of (modified) observation consistency remains open.

Abstract

Conditions preserving observability of specifications between the plant and its abstraction are essential for hierarchical supervisory control of discrete-event systems under partial observation. Observation consistency and local observation consistency were identified as such conditions. To preserve normality, only observation consistency is required. Although observation consistency preserves normality between the levels for normal specifications, for specifications that are not normal, observation consistency is insufficient to guarantee that the supremal normal sublanguage computed on the low level and on the high level coincide. We define modified observation consistency, under which the supremal normal sublanguages of different levels coincide. We show that the verification of (modified) observation consistency is PSPACE-hard for finite automata and undecidable for slightly more expressive models than finite automata. Decidability of (modified) observation consistency is an open problem. Hence we further discuss two stronger conditions that are easy to verify. Finally, we illustrate the conditions on an example of a railroad controller and on a case study of a part of an MRI scanner.