EI、Scopus 收录
中文核心期刊
段书用, 段浩东, 韩旭, 李昌洛, 欧阳衡, 李雨乐, 刘桂荣. 机器人关节非线性摩擦模型关键参数反求. 力学学报, 2022, 54(11): 3189-3202. DOI: 10.6052/0459-1879-22-252
引用本文: 段书用, 段浩东, 韩旭, 李昌洛, 欧阳衡, 李雨乐, 刘桂荣. 机器人关节非线性摩擦模型关键参数反求. 力学学报, 2022, 54(11): 3189-3202. DOI: 10.6052/0459-1879-22-252
Duan Shuyong, Duan Haodong, Han Xu, Li Changluo, Ouyang Heng, Li Yule, Liu Guirong. Inverse of key parameters of nonlinear friction model of robot joints. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(11): 3189-3202. DOI: 10.6052/0459-1879-22-252
Citation: Duan Shuyong, Duan Haodong, Han Xu, Li Changluo, Ouyang Heng, Li Yule, Liu Guirong. Inverse of key parameters of nonlinear friction model of robot joints. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(11): 3189-3202. DOI: 10.6052/0459-1879-22-252

机器人关节非线性摩擦模型关键参数反求

INVERSE OF KEY PARAMETERS OF NONLINEAR FRICTION MODEL OF ROBOT JOINTS

  • 摘要: 机器人关节非线性摩擦的准确描述对提高机器人轨迹精度、定位精度及其可靠性等具有重要理论意义和科学价值. 然而, 机器人关节通常包含电机、减速器、驱动器和传感器, 是一个复杂的机电耦合系统, 随服役时间及工况的变化, 机器人关节的摩擦参数也存在显著时变效应, 难以准确描述, 造成轨迹精度下降, 为机器人后期精度维护造成巨大困难. 因此, 本文定量评价了摩擦参数对机器人输出力矩的影响, 提出考虑时变效应的机器人关节非线性摩擦参数反求方法. 首先, 建立机器人关节一般非线性摩擦模型. 设计机器人关节恒速跟踪实验, 通过卡尔曼滤波对实验采集的数据进行处理, 进而建立关节速度和驱动电机电流之间的关系, 完成关节一般非线性摩擦模型建立. 其次, 择取非线性摩擦模型关键参数. 建立包含非线性摩擦的机器人动力学模型, 基于激励轨迹计算各关节力矩, 并对其开展灵敏度分析, 择取对关节力矩灵敏性较高的摩擦参数. 再次, 建立关节输出力矩和摩擦参数一一对应的数据集. 基于实际工况构建摩擦参数取值空间, 采用最优拉丁超立方法对摩擦参数采样, 并将其代入机器人动力学模型计算出相应的力矩, 从而求得关节输出力矩和摩擦参数一一对应的数据集. 最后, 建立反问题神经网络并对其进行训练, 实现非线性摩擦模型关键参数反求, 并进行验证. 研究结果表明关节非线性摩擦的准确描述减小了机器人低速运动换向时摩擦力矩突变对机器人轨迹的影响, 显著提升了机器人轨迹精度.

     

    Abstract: An accurate description of nonlinear friction of robot joints has important theoretical and scientific significance for improving trajectory accuracy, positioning accuracy and reliability of robot. However, the robot joints usually contain the motors, reducers, actuators and sensors, which are complex electromechanical coupling system. With the change of service time and working conditions, the friction parameters of robot joints also have significant time-varying effect, which is difficult to accurately describe, resulting in the decrease of trajectory accuracy and great difficulty for robot precision maintenance in the later stage. Therefore, this paper quantitatively evaluates the influence of friction parameters on the output torque of the robot, and proposes an inverse method for nonlinear friction parameters of the robot joints considering time-varying effects. Firstly, a general nonlinear friction model of the robot joint is established. The robot joint constant speed tracking experiment was designed, and the data collected by the experiment were processed by the Kalman filter. Then the relationship between the joint velocity and the driving motor current was established, and the general nonlinear friction model of the joint was established. Secondly, the key parameters of nonlinear friction model are selected. The dynamics model of robot containing nonlinear friction was established. The joint torques were calculated based on the excitation trajectory, and the friction parameters with high sensitivity to joint torques were selected for sensitivity analysis. Thirdly, a data set corresponding to the joint output torque and friction parameters is established. The friction parameter value space was constructed based on the actual working conditions, and the optimal Latin hypercube method was used to sample the friction parameters, which were substituted into the robot dynamics model to calculate the corresponding torques, and the one-to-one data set corresponding to the joint output torques and friction parameters were obtained. Finally, the inverse problem neural network is established and trained, and the key parameters of the nonlinear friction model are reversed and verified. The results illustrate that the accurate description of nonlinear joint friction reduces the influence of friction moment mutation on the trajectory of the robot, and significantly improves the trajectory accuracy.

     

/

返回文章
返回