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<p>In industrial control systems, such as power transmission facilities and water treatment plants, Programmable Logic Controllers (PLCs) can work consistently and stably over long periods if there are no faults. Black-box identification aims to automatically construct Petri net models with the help of I/O signals from PLC devices only. The main challenge is how to convert the infinitely long PLC signals into an event sequence, which is the foundation for subsequent modeling. The current algorithms are confronted with a number of challenges, including an exponential increase in the number of transitions, high time complexity, and susceptibility to noisy signals. To solve these problems, this paper proposes a new method for converting PLC signals into a transition sequence. The method is based on the principles of Boolean absorption law, which filters out noise information in the I/O signals. Then firing functions representing input–output causality are constructed from the filtered signals. Finally, the original signal sequence is traversed to generate a transition sequence. The experimental results show that these methods can rapidly identify a transition sequence. Compared to traditional methods, the proposed algorithms have polynomial time complexity.</p>

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PLC transition sequence identification based on logical reduction

  • 期刊论文

  • 发表日期：

    2025年8月12日

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  • Yue Luo,
  • Jianhong Ye,
  • Jiazhong Zhou,
  • Jia Liu,
  • Linping Jiang

摘要

In industrial control systems, such as power transmission facilities and water treatment plants, Programmable Logic Controllers (PLCs) can work consistently and stably over long periods if there are no faults. Black-box identification aims to automatically construct Petri net models with the help of I/O signals from PLC devices only. The main challenge is how to convert the infinitely long PLC signals into an event sequence, which is the foundation for subsequent modeling. The current algorithms are confronted with a number of challenges, including an exponential increase in the number of transitions, high time complexity, and susceptibility to noisy signals. To solve these problems, this paper proposes a new method for converting PLC signals into a transition sequence. The method is based on the principles of Boolean absorption law, which filters out noise information in the I/O signals. Then firing functions representing input–output causality are constructed from the filtered signals. Finally, the original signal sequence is traversed to generate a transition sequence. The experimental results show that these methods can rapidly identify a transition sequence. Compared to traditional methods, the proposed algorithms have polynomial time complexity.