Combining Advantages from Parameters in Modeling and Control of Discrete Event Systems

Abstract

Although Finite-State Automata (FSA) have been successfully used in modeling and control of Discrete Event Systems (DESs), they are limited to represent complex and advanced features of DESs, such as context recognition and switching. The literature has suggested that a FSA can nevertheless be enriched with parameters properly collected from the modeled system, so that this favors design and control. A parameter can be embedded either on transitions or states. However, each approach is structured within a specific framework, so that their comparison and integration are not straightforward and they may lead to different control solutions, modeled, computed and implemented using distinct strategies. In this paper, we show how to combine advantages from parameters in modeling and control of DESs. Each approach is structured and their advantages are identified and exemplified. Then, we propose a conversion method that allows to translate a design-friendly model into a synthesisefficient structure. Examples illustrate the approach.

Modelling and control of manufacturing systems subject to context recognition and switching

“…A first attempt to theoretically combine advantages from EpFSA and SpFSA was made (Southier et al 2019). However, in that study, we do not consider: modularsynthesis advantages, modular conversion, tool implementation, and test cases.…”