Communicating Processes with Data for Supervisory Coordination

TL;DR

This paper develops a process theory with data for supervisory coordination in distributed systems, enhancing expressivity and communication modeling, demonstrated through an industrial case study.

Contribution

It introduces a data-supported process theory for supervisory control, improving modeling of information flows and coordination requirements in complex systems.

Findings

Enhanced modeling of communication and data flows in supervisory control

Successful application to industrial maintenance coordination case study

Framework increases expressivity for formal system design

Abstract

We employ supervisory controllers to safely coordinate high-level discrete(-event) behavior of distributed components of complex systems. Supervisory controllers observe discrete-event system behavior, make a decision on allowed activities, and communicate the control signals to the involved parties. Models of the supervisory controllers can be automatically synthesized based on formal models of the system components and a formalization of the safe coordination (control) requirements. Based on the obtained models, code generation can be used to implement the supervisory controllers in software, on a PLC, or an embedded (micro)processor. In this article, we develop a process theory with data that supports a model-based systems engineering framework for supervisory coordination. We employ communication to distinguish between the different flows of information, i.e., observation and supervision, whereas we employ data to specify the coordination requirements more compactly, and to increase the expressivity of the framework. To illustrate the framework, we remodel an industrial case study involving coordination of maintenance procedures of a printing process of a high-tech Oce printer.