Modelling and Control Methodologies for Automated Systems Based on Regulation Control and Coloured Petri Nets

Abstract

Industry 4.0 and smart manufacturing have brought new interesting possibilities and chal-lenges to the industrial environment. One of these challenges is the large-scale automation of increasingly complex systems with minimal set-up time and flexibility, while allowing the in-tegration of components and systems from different manufacturers for production customiza-tion. To face this challenge, control approaches based on Discrete Event Systems (DES), such as Supervisory Control Theory (based on either, automata or Petri nets), Generalized Mutual Exclusions Constraints (GMEC) and Petri net-based Regulation Control, may provide con-venient solutions. However, few works have been reported in the literature for the case of complex systems and implementation in real plants. The latter opens up an important area of research opportunities. In this dissertation work, methodologies for modelling and control of automated systems based on the Regulation Control approach using interpreted Petri nets are studied. Using this approach, it is possible to capture the information of a system through its inputs and outputs, which allows to force sequences and generate more efficient controllers that can be directly translated to a Programmable Logic Controller (PLC). Through case studies, the effective-ness of these methodologies when implemented in more complex systems is demonstrated. Furthermore, the use of coloured Petri nets is proposed for the modelling of customized pro-duction systems. For this purpose, a new approach based on tensor arrays is introduced to express the colored Petri nets, allowing the use of algebraic techniques in the analysis of these systems.