融合扩张状态观测器的微型磁螺旋机器人航向自适应路径跟踪控制

刁建华; 范增华; 王鹤凤; 荣伟彬; 王乐锋; 张坤

doi:10.7652/xjtuxb202611008

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融合扩张状态观测器的微型磁螺旋机器人航向自适应路径跟踪控制

更新时间：2026-11-09

- 融合扩张状态观测器的微型磁螺旋机器人航向自适应路径跟踪控制
- Heading-Adaptive Path-Tracking Control for Magnetic Helical Microrobots Incorporating an Extended State Observer
- 西安交通大学学报 2026年60卷第11期页码：84-94
- 作者机构：
  
  山东理工大学机械工程学院，255049，山东淄博
  哈尔滨工业大学机器人技术与系统全国重点实验室，150000，哈尔滨
- 作者简介：
  
  刁建华（1998—），男，硕士生；
  范增华（通信作者），男，副教授，博士生导师。
- 基金信息：
  
  山东省自然科学基金资助项目(ZR2023ME060;ZR2025MS757)
- DOI：10.7652/xjtuxb202611008
  中图分类号： TP242.2
- 收稿：2026-02-02，
  
  网络首发：2026-06-23，
  
  纸质出版：2026-11-10
- 稿件说明：
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刁建华, 范增华, 王鹤凤, 等. 融合扩张状态观测器的微型磁螺旋机器人航向自适应路径跟踪控制[J/OL]. 西安交通大学学报,2026,60 (11):84-94. https://doi.org/10.7652/xjtuxb202611008.

DIAO Jianhua, FAN Zenghua, WANG Hefeng, et al. Heading-Adaptive Path-Tracking Control for Magnetic Helical Microrobots Incorporating an Extended State Observer[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (11):84-94. https://doi.org/10.7652/xjtuxb202611008.
刁建华, 范增华, 王鹤凤, 等. 融合扩张状态观测器的微型磁螺旋机器人航向自适应路径跟踪控制[J/OL]. 西安交通大学学报,2026,60 (11):84-94. https://doi.org/10.7652/xjtuxb202611008. DOI：

DIAO Jianhua, FAN Zenghua, WANG Hefeng, et al. Heading-Adaptive Path-Tracking Control for Magnetic Helical Microrobots Incorporating an Extended State Observer[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (11):84-94. https://doi.org/10.7652/xjtuxb202611008. DOI：

摘要

为解决微型磁螺旋机器人在低雷诺数液体环境中受路径几何复杂性与参数不确定性导致鲁棒性不足的问题，提出一种基于扩张状态观测器（ESO）的微型机器人航向自适应路径跟踪控制方法。首先，设计一种锥形尾的微型磁螺旋机器人，基于阻力理论，建立微型机器人动力学模型，揭示推进力、阻力与系统扰动对微型机器人运动速度的影响。然后，建立ESO与自适应航向控制器（AHC）协同控制的自适应路径跟踪控制器（APTC），通过ESO对系统进行扰动估计与偏差监测，AHC根据估计的扰动和偏差进行自适应航向调节，通过前馈补偿优化路径跟踪精度。最后，构建磁驱动控制系统，通过不同路径跟踪实验对比分析APTC的控制性能。实验结果表明：在V形、U形和O形路径下，APTC相较于模型预测控制（MPC），其平均绝对误差降低了3.6%～10.8%，均方根误差降低了3.4%～7.7%；在迷宫路径跟踪实验中，平均绝对误差与均方根误差分别降至187、230μm。研究结果表明，APTC能够应对低雷诺数液体环境的复杂路径跟踪的误差积累，提升微型机器人路径跟踪的精度与鲁棒性。

Abstract

To address the inadequate robustness of magnetic helical microrobots in low-Reynoldsnumber fluid environments caused by complex path geometries and parameter uncertainties

a heading-adaptive path-tracking control method based on an extended state observer (ESO) is proposed.First

a conical-tailed magnetic helical microrobot is designed

and its dynamics model is established based on the resistive force theory (RFT) to reveal the effects of propulsion

drag forces

and system disturbances on its locomotion velocity.Then

an adaptive path tracking controller (APTC) is developed by synergizing the ESO with an adaptive heading controller (AHC) .In this scheme

the ESO estimates system disturbances and monitors tracking deviations in real time

while the AHC performs adaptive heading adjustment based on the estimated disturbances and deviations.Furthermore

feedforward compensation is introduced to optimize the path-tracking accuracy.Subsequently

a magnetic actuation system was constructed

and comparative path tracking experiments were conducted to evaluate the performance of the proposed APTC.Experimental results demonstrate that for V-

U-

and O-shaped paths

compared to model predictive control (MPC)

the APTC reduces the mean absolute error and root mean square error by 3.6%—10.8% and 3.4%—7.7%

respectively.In maze path-tracking experiments

the MAE and RMSE are further reduced to 187μm and 230 μm

respectively.The study indicates that the APTC can effectively mitigate error accumulation during complex path tracking in low-Reynolds-number fluid environments

thereby enhancing the tracking accuracy and robustness of microrobots.

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