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Hybrid Tension and Configuration Control of Cable-Driven Hyper-Redundant Robots for High Accuracy and Stability

Zhenpu Zhu, Ziqing Li, Guoying Gu

发表年份
2025
引用次数
1

摘要

Due to the advantages of dexterity and adaptability, cable-driven hyper-redundant robots (CDHRRs) are promising for detection in confined spaces like narrow internal cavities. However, due to redundant degrees of freedom (DoFs), CDHRRs are susceptible to the singular configuration, which aggravates the difficulty of high-accuracy control and high-stable motion. To solve these problems, this work proposes hybrid tension and configuration control to improve motion accuracy and stability. Firstly, a CDHRR model with structural optimization and friction reduction is developed. The quasi-static and cable-hole length estimation models are obtained, including cable-hole friction, cable-hole interval, and cable deformation. Subsequently, single and multi-segment controllers are designed. The controller can distribute tension in the expected range with the above design while featuring high accuracy, responsiveness, and stability. The control algorithm optimizes configuration with an average error under 1.00<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula>. Moreover, the controller reaches the target with controllable forces in 1.0 s and flattens the fluctuations within 0.3 s. The controller can be implemented into automatic zeroing and tip loading. Experimental results demonstrate that the proposed controller features speedy automatic zeroing (in 4 mins) and low angle tracking errors (less than 1.50<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula>) under various tip loads.

关键词

Stability (learning theory)RobotTension (geology)Control theory (sociology)Computer scienceControl (management)Control engineeringEngineeringArtificial intelligenceMaterials science

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