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Model predictive control for discrete and continuous timed Petri nets

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Abstract

The goal of this paper is to propose a unique control method that permits the evolution of both timed continuous Petri net (TCPN) and T-timed discrete Petri net (T-TDPN) from an initial state to a desired one. Model predictive control (MPC) is a robust control scheme against perturbation and a consistent real-time constraints method. Hence, the proposed approach is studied using the MPC. However, the computational complexity may prevent the use of the MPC for large systems and for large prediction horizons. Then, the proposed approach provides some new techniques in order to reduce the high computational complexity; among them one is taking constant control actions during the prediction.

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Authors and Affiliations

  1. Laboratory GREAH, University of Le Havre, Le Havre, France

    Marwa Taleb, Edouard Leclercq & Dimitri Lefebvre

Authors
  1. Marwa Taleb
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  2. Edouard Leclercq
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  3. Dimitri Lefebvre
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Corresponding author

Correspondence to Marwa Taleb.

Additional information

This work was supported by the region Haute-Normandie Project (Nos. CPER-SER-DDSMRI 2013, 2014 and CPER-SER-SEL 2015).

Recommended by Associate Editor Hong-Nian Yu

Marwa Taleb received the M. Sc. degree in telecommunications from National Engineering School of Tunis, Tunisia in 2012. She received the Ph.D. degree in computer engineering, automation control and signal processing from University of Le Havre, France in 2016. She is actually temporarily attached to education and research with the Research Group on Electrical Engineering and Automatic Control.

Her research interests include dynamic systems, Petri nets and model predictive control.

Edouard Leclercq received the B. Sc. degree in physics and mathematics from Paris Educational District, France in 1987, the M. Sc. degree in electronics from University of Rouen, France in 1994, and the Ph.D. degree in automation from University of Le Havre, France in 1999. Since 1999 he is a lecturer at the Faculty of Sciences and Technology of Le Havre, France. Since 1999 he is with the G.R.E.A.H. (Electric and Automatic Engineering Research Group).

His research interests include modeling, control and fault detection, neural networks and Petri nets.

Dimitri Lefebvre graduated from the Ecole Centrale of Lille, France in 1992. He received a Ph.D. degree in automatic control and computer science from University of Sciences and Technologies, Lille in 1994, and a HDR from University of Franche Comt Belfort, France in 2000. Since 2001, he has been a professor at Institute of Technology and Faculty of Sciences, University Le Havre, France. He is with the Research Group on Electrical Engineering and Automatic Control (GREAH) and from 2007 to 2012 he was the head of the group.

His research interests include Petri nets, learning processes, adaptive control, fault detection and diagnosis and its applications to electrical engineering

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Taleb, M., Leclercq, E. & Lefebvre, D. Model predictive control for discrete and continuous timed Petri nets. Int. J. Autom. Comput. 15, 25–38 (2018). https://doi.org/10.1007/s11633-016-1046-7

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  • DOI: https://doi.org/10.1007/s11633-016-1046-7

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