Methodology for fast prototyping of distributed real-time systems

Sahraoui, Zakaria; Labed, Abdenour

doi:10.1109/isia55826.2022.9993590

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…Design and implementation of Distributed Control Systems involve many challenging issues including network-induced delays, time-varying topology or throughput, or increasing complexity. The need to address these issues has stimulated the development of methodologies for modeling, analysis and synthesis of DCSs [5], which standardly rely on computational tools based on Java, C++ or MATLAB/Simulink [2,51,52] to perform simulations based on resulting models. Such approaches have enabled model-based analyses of DCS throughput/response time [53,54].…”

Section: Methodology For Modeling and Analysis Of Distributed Control...mentioning

confidence: 99%

Modeling and Analysis of Distributed Control Systems: Proposal of a Methodology

Tkáčik,

Jadlovský,

Jadlovská

et al. 2023

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A Distributed Control System is a concept of Network Control Systems whose applications range from industrial control systems to the control of large physical experiments such as the ALICE experiment at CERN. The design phase of the Distributed Control Systems implementation brings several challenges, such as predicting the throughput and response of the system in terms of data-flow. These parameters have a significant impact on the operation of the Distributed Control System, and it is necessary to consider them when determining the distribution of software/hardware resources within the system. This distribution is often determined experimentally, which may be a difficult, iterative process. This paper proposes a methodology for modeling Distributed Control Systems using a combination of Finite-State Automata and Petri nets, where the resulting model can be used to determine the system’s throughput and response before its final implementation. The proposed methodology is demonstrated and verified on two scenarios concerning the respective areas of ALICE detector control system and mobile robotics, using the MATLAB/Simulink implementation of created models. The methodology makes it possible to validate various distributions of resources without the need for changes to the physical system, and therefore to determine the appropriate structure of the Distributed Control System.

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