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基于期望轨迹修正的机械臂无传感器柔顺控制
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江苏高校“青蓝工程”项目(苏教师[2023]27号);江苏省徐州市科技计划项目(KC21003)


Sensorless Compliance Control of Manipulator Based on Expected Trajectory Modification
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    摘要:

    为了提高机械臂与环境交互时的接触力控制精度,提出基于期望轨迹修正的无传感器主动柔顺控制方法。针对传统参数辨识方法损失面函数鞍点多、易陷入局部最优、计算量大等问题,基于牛顿-欧拉法得到机械臂由外向内递归的参数辨识方法,该方法可实现参数的分步分批辨识;针对机械臂与环境交互时的主动柔顺控制问题,使用位置阻抗控制原理对期望轨迹进行修正,设计了参数不确定条件下的非奇异终端滑模控制;最后,基于Lyapunov理论证明控制系统的稳定性。经实验验证,基于传统辨识方法的反算力矩累计绝对误差为9.35 N·m,递归辨识方法的反算力矩累计绝对误差为1.05 N·m,说明参数递归辨识精度远高于传统辨识方法;在位置阻抗控制作用下,接触力在2.8 s达到设定值,误差波动范围为±0.4 N。实验结果验证了所提主动柔顺控制方法的优越性。

    Abstract:

    In order to improve the control accuracy of the contact force when the manipulator interacts with the environment, a sensorless active compliance control method based on expected trajectory correction was proposed. Aiming at the problems of traditional parameter identification methods, such as many saddle points of loss surface function, easy to fall into local optimization, and large calculation amount, based on Newton-Euler method, a recursive parameter identification method of manipulator from outside to inside was proposed, which could realize the step-by-step and batch identification of parameters. Aiming at the active compliance control problem when the manipulator interacts with the environment, the position impedance control principle was used to modify the desired trajectory, and the nonsingular terminal sliding mode control was designed under the condition of parameter uncertainty. Finally, the stability of the control system was proved based on Lyapunov theory. Through experimental verification, the cumulative absolute error of the back calculation torque based on the traditional identification method is 9.35 N·m, while it is 1.05 N·m based on the recursive identification method, which indicates that the accuracy of the parameter recursive identification is much higher than that of the traditional identification method. Under the control of position impedance , the contact force reaches the set value in 2.8 s, and the error fluctuation range is ±0.4 N.The experimental results verify the superiority of the active compliance control method.

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朱敬花,邵珠枫.基于期望轨迹修正的机械臂无传感器柔顺控制[J].机床与液压,2023,51(21):84-90.
ZHU Jinghua, SHAO Zhufeng. Sensorless Compliance Control of Manipulator Based on Expected Trajectory Modification[J]. Machine Tool & Hydraulics,2023,51(21):84-90

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  • 在线发布日期: 2023-11-29
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