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Control design for untimed Petri nets using Markov Decision Processes

Author

Listed:
  • Cherki Daoui
  • Dimitri Lefebvre

Abstract

Design of control sequences for discrete event systems (DESs) has been presented modelled by untimed Petri nets (PNs). PNs are well-known mathematical and graphical models that are widely used to describe distributed DESs, including choices, synchronizations and parallelisms. The domains of application include, but are not restricted to, manufacturing systems, computer science and transportation networks. We are motivated by the observation that such systems need to plan their production or services. The paper is more particularly concerned with control issues in uncertain environments when unexpected events occur or when control errors disturb the behaviour of the system. To deal with such uncertainties, a new approach based on discrete time Markov decision processes (MDPs) has been proposed that associates the modelling power of PNs with the planning power of MDPs. Finally, the simulation results illustrate the benefit of our method from the computational point of view.

Suggested Citation

  • Cherki Daoui & Dimitri Lefebvre, 2017. "Control design for untimed Petri nets using Markov Decision Processes," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(4), pages 27-43.
    • Handle: RePEc:wut:journl:v:4:y:2017:p:27-43:id:1319
    DOI: 10.5277/ord170402
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    References listed on IDEAS

    as
    1. M. Abbad & C. Daoui, 2003. "Hierarchical algorithms for discounted and weighted Markov decision processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 58(2), pages 237-245, November.
    2. Wolfram Wiesemann & Daniel Kuhn & Berç Rustem, 2013. "Robust Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 38(1), pages 153-183, February.
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