VGBL-ADRC based velocity–tension coordinated winding control for Open-Type abrasive belt rail grinding robot
Purpose Sensing constraints, strong velocity–tension (V-T) coupling, and rail-defect-induced disturbances make V-T coordinated winding control challenging for open-type abrasive-belt rail grinding robots. This paper aims to propose a tension-observer-enhanced variable-gain bi-layer active disturbance rejection control (VGBL-ADRC) framework to mitigate V-T coupling and achieve coordinated winding control under external disturbances. Design/methodology/approach The model-based tension observer reconstructs belt tension online from encoder-derived kinematics, which provides sensorless feedback and eliminates the need for dedicated tension sensors in the rail-grinding environment. Building on this, the error-dependent variable-gain bi-layer ADRC is implemented in the velocity and tension loops. Nonlinear extended state observers incorporating smooth error-driven gains, in conjunction with the corresponding variable-gain feedback laws, not only enhance the disturbance rejection capability and tracking performance but also simultaneously constrain noise amplification. Such a synergistic effect mitigates dynamic coupling between belt velocity and tension, thereby facilitating coordinated V-T winding control. Findings ADAMS–Simulink co-simulation under corrugation and localized defects shows that the belt speed fluctuation is kept within 2% and the maximum speed error is limited to 0.4%. Track experiments further demonstrate the advantage over conventional ADRC: in forward grinding, the proposed method reduces the velocity RMSE by 52.9% and the tension RMSE by 40.9%, and lowers the steady-state MAE by 71.9% in speed and 70.9% in tension. Similar improvements with consistent trends are observed in reverse grinding. Originality/value The proposed strategy provides a practical sensorless solution for disturbance-dominated, strongly coupled winding control in abrasive belt rail grinding and can be extended to other harsh industrial grinding environments.
Authors
- Lei Hao
- Qi Li (ORCID: https://orcid.org/0000-0001-8776-8730)
- Kang Xu
- Qingsong Chen (ORCID: https://orcid.org/0000-0001-9313-9981)
- J T Li
- Haoze Tang
- Meng Nie
- Yixian Ding
Institutions
- Beijing Jiaotong University (CN)
Publication Details
- Journal
- Industrial Robot the international journal of robotics research and application
- Published
- 2026-06-18
- DOI
- https://doi.org/10.1108/ir-12-2025-0480
- Primary Topic
- Advanced Surface Polishing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00