Author(s):
Gomes, Luís ; Natário, Diogo ; Costa, Anikó ; Barros, João Paulo ; Campos-Rebelo, Rogério
Date: 2024
Persistent ID: http://hdl.handle.net/10362/170250
Origin: Repositório Institucional da UNL
Project/scholarship:
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT;
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00066%2F2020/PT;
Subject(s): automation systems; discrete-event systems; Petri nets; Engineering(all); Computer Science Applications; Instrumentation
Description
Funding Information: This work was funded by the Portuguese Agency Fundação para a Ciência e a Tecnologia (FCT) program, in the framework of project Center of Technology and Systems (CTS) UIDB/00066/2020 / UIDP/00066/2020. Publisher Copyright: © 2024 by the authors.
Controllers for discrete-event systems are commonly designed using state-based formalisms, like state diagrams and Petri nets. These formalisms are strongly supported by the concept of events, which, from an automation system perspective, can be associated with a simple change in the value of a signal or more complex behavioral evolutions of the signals. In this paper, the characterization of several types of events is proposed, associated with different types of signals, such as Boolean and multivalued signals. The major goal of this characterization is to improve the compactness of the model, benefiting the editing and visual interpretation of the graphical model but keeping precise execution semantics, which in turn allows for the use of computational tools covering the different stages of system development. The behavioral model of the controller is produced using a non-autonomous class of Petri nets, the IOPT nets, and the associated IOPT-Tools, which supports the specification, simulation, property verification, and automatic code generation ready to be deployed into implementation platforms. All the types of proposed events have a behavioral sub-model executed concurrently with the main model of the controller. An application example is provided to illustrate some of the advantages of the adoption of the proposed approach, encapsulating the behavioral dependencies on the evolution of input signals into events.
