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<p> This paper presents a five degrees of freedom two-layered vertical eight-cable-driven parallel robot (CDPR), specifically developed for machining applications on large vertical surfaces. To address the control challenges posed by cable flexibility, nonlinear dynamics, and external disturbances during contact-based tasks, an Adaptive Fuzzy Sliding Mode Controller (AFSMC) is proposed. This controller integrates a sliding mode framework with fuzzy logic to enhance robustness and adaptability while mitigating chattering. The system also employs a feedback mechanism combining an IMU and a neural network for pose estimation, and a non-iterative closed-form tension distribution algorithm for real-time implementation. Experimental validation confirms the controller’s effectiveness in trajectory tracking, interaction force regulation, and repeatability under dynamic and uncertain conditions. The results demonstrate the robot’s suitability for tasks such as polishing, blasting or waterjet machining on large vertical surfaces, where moderate accuracy and robustness are essential.</p>

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The Two-Layered Vertical Cable-Driven Parallel Robot for Machining Controlled by Adaptive Fuzzy Sliding Mode Controller

  • 期刊论文

  • 发表日期：

    2026年3月11日

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  • Thanh-Hai Nguyen,
  • Kwan-Woong Gwak,
  • Dinh Ba Pham,
  • Duc Hai Nguyen

摘要

This paper presents a five degrees of freedom two-layered vertical eight-cable-driven parallel robot (CDPR), specifically developed for machining applications on large vertical surfaces. To address the control challenges posed by cable flexibility, nonlinear dynamics, and external disturbances during contact-based tasks, an Adaptive Fuzzy Sliding Mode Controller (AFSMC) is proposed. This controller integrates a sliding mode framework with fuzzy logic to enhance robustness and adaptability while mitigating chattering. The system also employs a feedback mechanism combining an IMU and a neural network for pose estimation, and a non-iterative closed-form tension distribution algorithm for real-time implementation. Experimental validation confirms the controller’s effectiveness in trajectory tracking, interaction force regulation, and repeatability under dynamic and uncertain conditions. The results demonstrate the robot’s suitability for tasks such as polishing, blasting or waterjet machining on large vertical surfaces, where moderate accuracy and robustness are essential.