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为了能够利用变刚度关节实现对机器人动态特性的调整,需要对关节的动态刚度进行有效的辨识和控制.本文首先根据机器人变刚度关节的结构特点建立了简化模型,并对其刚度输出特性表达做出假设;然后对模型中的力矩相关参数进行解耦,消除了关节刚度调节参数对力矩的影响,获取与刚度辨识相关的归一化力矩;利用泰勒展开对归一化力矩进行线性化处理,采用卡尔曼滤波器进行了系数优化,并进一步实现了对关节动态刚度的辨识.仿真中该刚度在线辨识方法可以将辨识误差控制在±2%以内,在实现动态刚度辨识的基础上研究了基于前馈的刚度闭环控制方法,通过仿真实验验证了该方法对于机器人关节刚度闭环控制是有效的.
In order to be able to use the variable stiffness joint to adjust the robot’s dynamic characteristics, the dynamic stiffness of the joint needs to be effectively identified and controlled.This paper firstly establishes a simplified model according to the structural characteristics of the variable stiffness joint of the robot, Then, the torque-related parameters in the model are decoupled to eliminate the influence of the joint stiffness adjustment parameters on the moment and obtain the normalized moment related to the stiffness identification. The normalized moment is linearized by Taylor’s expansion, The Kalman filter is used to optimize the coefficient and to further realize the joint dynamic stiffness identification.The online identification of the stiffness in the simulation can control the identification error within ± 2%. Based on the realization of dynamic stiffness identification, The closed-loop control method of feedforward stiffness is validated by simulation experiments. This method is effective for closed-loop control of robot joint stiffness.