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<p>Real applications such as supply chains, flexible industrial systems, networked control, and urban transport often exhibit a discrete event system (DESs) structure. These systems have variable states which change at discrete times. However, as these systems evolve, a variety of limits have appeared. In this paper, we consider networks of timed event graphs (NTEGs) with disturbance transitions, which are subject to generalized mutual exclusion constraints (GMECs). An algebraic method for designing control laws to guarantee these constraints is proposed. To this end, Min-Plus algebra formalisms are used to formalize the&#xa0;control strategy and to deduce the corresponding controllers. The&#xa0;calculated control laws are translated into monitor places and&#xa0;connected to the initial NTEGs model to prevent violation of GMECs.&#xa0;The developed approaches in this study are applied to manage the&#xa0;replenishment policy of a supply chain in the presence of disturbances.</p>

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Design of control laws to meet generalized mutual exclusion constraints in a network of timed event graphs with disturbances using dioid algebra

  • 期刊论文

  • 发表日期：

    2025年5月7日

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  • S. Bouazza,
  • S. Amari

摘要

Real applications such as supply chains, flexible industrial systems, networked control, and urban transport often exhibit a discrete event system (DESs) structure. These systems have variable states which change at discrete times. However, as these systems evolve, a variety of limits have appeared. In this paper, we consider networks of timed event graphs (NTEGs) with disturbance transitions, which are subject to generalized mutual exclusion constraints (GMECs). An algebraic method for designing control laws to guarantee these constraints is proposed. To this end, Min-Plus algebra formalisms are used to formalize the control strategy and to deduce the corresponding controllers. The calculated control laws are translated into monitor places and connected to the initial NTEGs model to prevent violation of GMECs. The developed approaches in this study are applied to manage the replenishment policy of a supply chain in the presence of disturbances.