Title: A new transformation approach for complex systems modelling and simulation: application to industrial control system

Authors: Noureddine Seddari; Sofiane Boukelkoul; Abdelghani Bouras; Mohamed Belaoued; Mohammed Redjimi

Addresses: LICUS Laboratory, Department of Computer Science, University of 20 August 1955-Skikda, 21000 Skikda, Algeria; LIRE Laboratory, Department of Software Technologies and Information Systems, University of Abdelhamid Mehri-Constantine 2, 25000 Constantine, Algeria ' LIRE Laboratory, Department of Software Technologies and Information Systems, University of Abdelhamid Mehri-Constantine 2, 25000 Constantine, Algeria ' Department of Industrial Engineering, Alfaisal University, Riyadh 12714, Saudi Arabia ' LICUS Laboratory, Department of Computer Science, University of 20 August 1955-Skikda, 21000 Skikda, Algeria ' LICUS Laboratory, Department of Computer Science, University of 20 August 1955-Skikda, 21000 Skikda, Algeria

Abstract: Due to the increasing importance of complex systems, the problems of modelling and simulation (M&S) of these systems, their approaches and solutions have been studied extensively these last years. In this paper, we present a novel approach to modelling and simulation of discrete event dynamic systems (DEDS), based on the combination of discrete event systems specification (DEVS) and agent group role (AGR). In this study, the DEVS atomic models are transformed into agents and the DEVS coupled models into groups of agents. Thus, we provide a set of procedures and functions that allow the systematic transformation from DEVS into AGR models in order to be implemented in multi-agent platforms. The proposed approach was validated by a case study, an application in the water supply used in natural gas liquefaction process.

Keywords: complex systems; discrete event dynamic systems; DEDS; discrete event systems specification; DEVS; modelling and simulation; M&S; agent group role; AGR model.

DOI: 10.1504/IJSPM.2021.113073

International Journal of Simulation and Process Modelling, 2021 Vol.16 No.1, pp.34 - 48

Received: 21 May 2019
Accepted: 14 May 2020
Published online: 17 Feb 2021 *

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