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<p>This paper presents an adaptive hybrid force-position control method for wheel-spoke grinding robots, addressing two critical industry challenges: (1) path-surface mismatch causing localized over/under-grinding, and (2) unstable contact pressure leading to poor surface finish. The proposed method integrates a disturbance observer (DOB) with nonsingular fast terminal sliding mode control (NFTSMC), featuring dual-loop innovation: In the force-control loop, a recurrent neural network (RNN) dynamically adjusts impedance parameters to maintain constant grinding force; in the position-control loop, the DOB-enhanced NFTSMC achieves precise trajectory tracking while rejecting disturbances. Experimental validation on automotive wheel spokes demonstrates superior performance: position tracking error reduced to <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(&lt;0.4^{\circ }\)</EquationSource> </InlineEquation> (42<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\%\)</EquationSource> </InlineEquation> improvement vs. PID control), steady-state force error <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(&lt;1\)</EquationSource> </InlineEquation>N, and surface roughness Ra<InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\le 0.7\upmu\)</EquationSource> </InlineEquation>&#xa0; m (meeting ISO 1302 grinding standards). The control system shows 40<InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\%\)</EquationSource> </InlineEquation> faster convergence than conventional sliding mode methods without singularity issues. Experimental results demonstrate that the proposed adaptive variable impedance hybrid control achieves superior stability and surface quality in robotic spoke grinding tasks.</p>

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Adaptive variable impedance hybrid force-position control method for hub-spoke grinding robots

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月3日

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  • Shang Wei,
  • Zhang Ze-jian,
  • Yang Hao-yu,
  • Dang Xiao-hong,
  • Sun Jia-yu,
  • Gao Ting,
  • Pan Jun,
  • Ai Jia

摘要

This paper presents an adaptive hybrid force-position control method for wheel-spoke grinding robots, addressing two critical industry challenges: (1) path-surface mismatch causing localized over/under-grinding, and (2) unstable contact pressure leading to poor surface finish. The proposed method integrates a disturbance observer (DOB) with nonsingular fast terminal sliding mode control (NFTSMC), featuring dual-loop innovation: In the force-control loop, a recurrent neural network (RNN) dynamically adjusts impedance parameters to maintain constant grinding force; in the position-control loop, the DOB-enhanced NFTSMC achieves precise trajectory tracking while rejecting disturbances. Experimental validation on automotive wheel spokes demonstrates superior performance: position tracking error reduced to \(<0.4^{\circ }\) (42 \(\%\) improvement vs. PID control), steady-state force error \(<1\) N, and surface roughness Ra \(\le 0.7\upmu\)   m (meeting ISO 1302 grinding standards). The control system shows 40 \(\%\) faster convergence than conventional sliding mode methods without singularity issues. Experimental results demonstrate that the proposed adaptive variable impedance hybrid control achieves superior stability and surface quality in robotic spoke grinding tasks.