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This study investigates the modeling and advanced control strategies for Cable-Driven Parallel Robots (CDPRs) operating on spherical surfaces, addressing challenges arising from varying angles on the spherical surface and the effects of gravity. Two control methods, the proportional-derivative (PD) and active disturbance rejection control (ADRC), were analyzed using MATLAB simulation with circular and spiral trajectories. The results demonstrate the effectiveness of both controllers, with ADRC exhibiting more robustness, precision, and adaptability, effectively managing disturbances and gravitational effects. While the PD is simpler, it struggles with overshoot and disturbance compensation and shows limitations in managing trajectory. A detailed comparative analysis of error minimization and torque performance further emphasized ADRC’s advantages. This research contributes to optimizing CDPR performance in complex environments, enhancing precision, stability, and control adaptability. The findings highlight ADRC as a robust alternative to conventional control strategies, offering broader applications for CDPRs in industrial and research settings requiring high accuracy and reliability.

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Modeling and Control of a Cable-Driven Parallel Robot on Spherical Surface

  • 会议论文

  • 发表日期：

    2025年

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  • Maitha AlQaydi,
  • Yahya Mohammed,
  • Lei Jin,
  • Ahmad AlAttar,
  • Mohamed Abduljawad,
  • Tarek Taha,
  • Dongming Gan

摘要

This study investigates the modeling and advanced control strategies for Cable-Driven Parallel Robots (CDPRs) operating on spherical surfaces, addressing challenges arising from varying angles on the spherical surface and the effects of gravity. Two control methods, the proportional-derivative (PD) and active disturbance rejection control (ADRC), were analyzed using MATLAB simulation with circular and spiral trajectories. The results demonstrate the effectiveness of both controllers, with ADRC exhibiting more robustness, precision, and adaptability, effectively managing disturbances and gravitational effects. While the PD is simpler, it struggles with overshoot and disturbance compensation and shows limitations in managing trajectory. A detailed comparative analysis of error minimization and torque performance further emphasized ADRC’s advantages. This research contributes to optimizing CDPR performance in complex environments, enhancing precision, stability, and control adaptability. The findings highlight ADRC as a robust alternative to conventional control strategies, offering broader applications for CDPRs in industrial and research settings requiring high accuracy and reliability.