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Research into the Beetle Antennae Optimization-Based PID Servo System Control of an Industrial Robot

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  • Tian Ji

    (School of Applied Science and Technology, Hainan University, Danzhou 571737, China)

  • Haoran Wei

    (School of Applied Science and Technology, Hainan University, Danzhou 571737, China)

  • Jun Wang

    (School of Applied Science and Technology, Hainan University, Danzhou 571737, China)

  • Shaoqing Tian

    (School of Applied Science and Technology, Hainan University, Danzhou 571737, China)

  • Yi Yao

    (School of Applied Science and Technology, Hainan University, Danzhou 571737, China)

  • Shukai Hu

    (School of Applied Science and Technology, Hainan University, Danzhou 571737, China)

Abstract

Industrial robot speed control remains a critical aspect for efficient operations, especially given the challenges of nonlinearity and multivariable characteristics inherent to servo motor control systems, as well as energy inefficiencies due to a lack of automatic speed control. This study refines an existing control algorithm, beetle antennae optimization (BAO), by integrating elements of particle swarm optimization (PSO) and a beetle antennae search algorithm (BAS), further enhanced by chaos mapping and an adaptive weighting factor. These modifications aim to improve the algorithm’s search capabilities and mitigate the risks of settling into local optima. Unlike previous iterations, this study includes rigorous dynamic and stability analyses focusing on key performance metrics such as settling time, overshoot, and steady-state error. Comparative Simulink/MATLAB modeling demonstrates that the enhanced BAO algorithm significantly outperforms traditional PID control, BAS, and adaptive weighted-PSO in reducing static error, overshoot, and adjustment time under various conditions, including scenarios with external disturbances. Our results indicate a 60% improvement in the optimization performance of speed curve metrics, confirming the enhanced efficacy and robustness of the robotic control system. This research offers valuable insights into the advantages of the refined BAO algorithm, providing a comprehensive basis for its practical application in industrial robotic control systems.

Suggested Citation

  • Tian Ji & Haoran Wei & Jun Wang & Shaoqing Tian & Yi Yao & Shukai Hu, 2023. "Research into the Beetle Antennae Optimization-Based PID Servo System Control of an Industrial Robot," Mathematics, MDPI, vol. 11(19), pages 1-24, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:19:p:4066-:d:1247367
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    References listed on IDEAS

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    1. Veerapandiyan Veerasamy & Noor Izzri Abdul Wahab & Rajeswari Ramachandran & Arangarajan Vinayagam & Mohammad Lutfi Othman & Hashim Hizam & Jeevitha Satheeshkumar, 2019. "Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller," Sustainability, MDPI, vol. 11(24), pages 1-20, December.
    2. Yuqi Fan & Junpeng Shao & Guitao Sun & Xuan Shao, 2020. "Improved Beetle Antennae Search Algorithm-Based Lévy Flight for Tuning of PID Controller in Force Control System," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-22, March.
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