现代制造工程 ›› 2026, Vol. 548 ›› Issue (5): 47-54.doi: 10.16731/j.cnki.1671-3133.2026.05.005

• 机器人技术 • 上一篇    下一篇

基于参数辨识的四足机器人单腿复合控制*

邹斌1, 朱雅光2, 刘宗耀1, 贾子健1   

  1. 1 长安大学高速公路筑养装备与技术教育部工程研究中心,西安 710064;
    2 煤炭智能开采与岩层控制全国重点实验室,北京 100013
  • 收稿日期:2025-08-01 出版日期:2026-05-18 发布日期:2026-06-04
  • 通讯作者: 朱雅光,博士,教授,博士生导师,主要研究方向为腿足机器人及智能控制系统。E-mail:zhuyaguang@chd.edu.cn
  • 作者简介:邹斌,硕士研究生,主要研究方向为机器人运动控制。E-mail:18170787059@163.com
  • 基金资助:
    *国家自然科学基金项目(62373064);煤炭智能开采与岩层控制全国重点实验室开放基金项目(SKLIS202414);陕西省科技创新引领计划项目(2024ZC-YYDP-114);陕西省重点研发计划项目(2024GX-ZDCYL-01-23)

Parameter identification-based composite control for a quadruped robot leg

ZOU Bin1, ZHU Yaguang2, LIU Zongyao1, JIA Zijian1   

  1. 1 Engineering Research Center of Highway Maintenance Equipment and Technology, Ministry of Education,Chang'an University,Xi'an 710064,China;
    2 State Key Laboratory of Intelligent Coal Mining and Strata Control,Beijing 100013,China
  • Received:2025-08-01 Online:2026-05-18 Published:2026-06-04

摘要: 四足机器人在高速动态运动时,其单腿系统面临强耦合非线性扰动,导致传统比例-微分(Proportional Derivative,PD)控制存在显著的跟踪误差,制约了机器人整体动态性能的发挥。为提升单腿在高速动态工况下的运动精度,提出并实现了一种基于动力学参数辨识的前馈-反馈复合控制方法。首先,基于拉格朗日方程建立包含关节摩擦的三自由度单腿动力学模型,并通过SymPyBotics库进行符号分析,以剔除冗余项,从而提取出系统的最小惯性参数集;其次,设计有限傅里叶级数形式的激励轨迹,以满足持续激励条件,采用融合参数先验信息的正则化加权最小二乘法离线辨识关键动力学参数;然后,基于辨识获得的动力学模型与期望运动状态,实时计算前馈力矩,主动补偿由科氏力、离心力、重力及关节摩擦引起的非线性扰动;同时,结合PD反馈控制器抑制模型不确定性及外部干扰,构建前馈预测与反馈修正协同作用的复合控制架构。为验证该方法的有效性,在单腿实验平台上开展对比实验,分别测试传统PD控制与复合控制的跟踪性能。在单腿实验平台上的对比实验结果表明,所辨识的动力学模型能准确预测关节力矩,验证轨迹下的力矩预测均方根误差较低;相较于传统PD控制,该复合控制方法使足端三维空间轨迹跟踪误差平均降低超过35 %,关节角度跟踪误差最大降低率为50.34 %。研究证实,所提出的复合控制方法能有效补偿高速运动中的非线性扰动,显著提高四足机器人单腿动态轨迹跟踪的精度。

关键词: 四足机器人, 单腿运动控制, 动力学参数辨识, 前馈-反馈复合控制, 非线性扰动, 轨迹跟踪

Abstract: During high-speed dynamic locomotion,the single leg system of a quadruped robot is subjected to strongly coupled nonlinear disturbances,which cause significant tracking errors in traditional Proportional-Derivative (PD) control and constrain the robot's overall dynamic performance. To enhance motion precision under such conditions,a feedforward-feedback composite control method based on dynamic parameter identification is proposed and implemented. Firstly,a three-degree-of-freedom single leg dynamic model incorporating joint friction is established based on the Lagrange equation. The system's minimum inertial parameter set is then extracted through symbolic analysis with the SymPyBotics library for the elimination of redundant terms. Secondly,an excitation trajectory,formulated as a finite Fourier series,is designed to satisfy the persistent excitation condition,and key dynamic parameters are identified offline using a regularized weighted least-squares method with prior parameter information. Then,a feedforward torque is calculated in real-time based on the identified dynamic model and desired motion state to actively compensate for nonlinear disturbances caused by Coriolis forces,centrifugal forces,gravity,and joint friction. Concurrently,model uncertainties and external disturbances are suppressed by a PD feedback controller,thus establishing a synergistic composite control architecture of feedforward prediction and feedback correction. The method's effectiveness is validated through comparative experiments on a single leg test platform,where the tracking performances of traditional PD and the proposed composite control are evaluated. Results indicate that the identified dynamic model can accurately predict joint torques, the root mean square error of torque prediction under the verified trajectory is relatively low. Compared to traditional PD control,the proposed composite control method reduces the average three-dimensional foot-end trajectory tracking error by exceeding 35 %,the maximum reduction in joint angle tracking error is 50.34 %. This research confirms that the proposed composite control method can effectively compensate for nonlinear disturbances during high-speed motion,leading to a significant improvement in the dynamic trajectory tracking accuracy of a quadruped robot's single leg.

Key words: quadruped robot, single-leg motion control, dynamic parameter identification, feedforward-feedback composite control, nonlinear disturbance, trajectory tracking

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