Graph-Based Orchestration of Service-Oriented Model-Based Control Systems

TL;DR

This paper introduces a graph-based approach for dynamically adapting control system architectures in service-oriented systems, enhancing flexibility, efficiency, and accuracy over traditional static methods.

Contribution

The paper presents a novel graph-based method for runtime control system architecture adaptation using service-oriented principles, enabling dynamic reconfiguration based on system state.

Findings

Improved control system flexibility

Reduced computation time

Enhanced control accuracy

Abstract

This paper presents a novel graph-based method for adapting control system architectures at runtime. We use a service-oriented architecture as a basis for its formulation. In our method, adaptation is achieved by selecting the most suitable elements, such as filters and controllers, for a control system architecture to improve control systems objective based on a predefined cost function. Traditional configuration methods, such as state machines, lack flexibility and depend on a predefined control system architecture during runtime. Our graph-based method allows for dynamic changes in the control system architecture, as well as a change in its objective depending on the given system state. Our approach uses a weighted, directed graph to model the control system elements and their interaction. In a case-study with a three-tank system, we show that by using our graph-based method for architecture adaptation, the control system is more flexible, has lower computation time, and higher accuracy than traditional configuration methods.