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Temperature-Controlled Laser Cutting of an Electrical Steel Sheet Using a Novel Fuzzy Logic Controller

Author

Listed:
  • Dinh-Tu Nguyen

    (Faculty of Mechanical Engineering, Can Tho University of Technology, Ninh Kieu District, Can Tho City 10000, Vietnam)

  • Yuan-Ting Lin

    (Department of Mechanical Engineering, National Central University, Jhong-Li District, Tao-Yuan City 32001, Taiwan)

  • Jeng-Rong Ho

    (Department of Mechanical Engineering, National Central University, Jhong-Li District, Tao-Yuan City 32001, Taiwan)

  • Pi-Cheng Tung

    (Department of Mechanical Engineering, National Central University, Jhong-Li District, Tao-Yuan City 32001, Taiwan)

  • Chih-Kuang Lin

    (Department of Mechanical Engineering, National Central University, Jhong-Li District, Tao-Yuan City 32001, Taiwan)

Abstract

A novel PID-type fuzzy logic controller (FLC) with an online fuzzy tuner was created to maintain stable in situ control of the cutting front temperature, aiming to enhance the laser process for thin non-oriented electrical steel sheets. In the developed controller, the output scaling factors and the universe of discourse were initially optimized using a hybrid of the particle swarm optimization and grey wolf optimization methods. The optimal parameters obtained were utilized in experiments involving the laser cutting of thin non-oriented electrical steel sheets, compared to an open-loop control system maintaining a constant cutting speed. The PID-type FLC with an online fuzzy tuner demonstrated a superior cutting quality, generating a smaller roundness and a reduced heat-affected zone (HAZ) through the in situ tuning of control parameters. Particularly, the HAZ width was significantly smaller than that reported in a previous study which used fuzzy gain scheduling for temperature control. Moreover, the cutting time was diminished by optimally adjusting the cutting speed using PID-type FLC with an online fuzzy tuner. Therefore, the accumulated heat in the steel sheet, particularly under high laser pulse frequencies, was effectively reduced, making it suitable for industrial applications.

Suggested Citation

  • Dinh-Tu Nguyen & Yuan-Ting Lin & Jeng-Rong Ho & Pi-Cheng Tung & Chih-Kuang Lin, 2023. "Temperature-Controlled Laser Cutting of an Electrical Steel Sheet Using a Novel Fuzzy Logic Controller," Mathematics, MDPI, vol. 11(23), pages 1-20, November.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:23:p:4769-:d:1287742
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    References listed on IDEAS

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    1. Narinder Singh & S. B. Singh, 2017. "Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance," Journal of Applied Mathematics, Hindawi, vol. 2017, pages 1-15, November.
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