Values of the dynamic parameters.

To improve the force/position control performance of robots in contact with the environment, this paper proposes a control scheme comprising dynamic parameter identification, trajectory scaling, and computed-torque control based on adaptive parameter estimation. Based on the Newton–Euler method, the dynamic equation and its regression matrix is obtained, which is helpful to reduce the order of the model. Subsequently, the least-square method is implemented to calculate the values of the basic parameters of the dynamics. The identified dynamic parameters are used as initial values in the adaptive parameter estimation to obtain the torque, and trajectory scaling is applied to control the contact force between the robot and the environment. Finally, the dynamic parameter identification method and control algorithm are verified by conducting a simulation. The results show that the comprehensive application can help improve the control performance of robots.为提升机器人与环境接触场景下的力位控制性能，本文提出一种集成动态参数辨识、轨迹缩放以及基于自适应参数估计的计算力矩控制的控制方案。基于牛顿-欧拉法（Newton–Euler method）推导得到机器人动力学方程及其回归矩阵，可有效降低模型阶数。随后采用最小二乘法（least-square method）计算动力学基本参数的取值。将辨识得到的动态参数作为自适应参数估计的初始值以求解控制力矩，并引入轨迹缩放策略调控机器人与环境间的接触力。最后通过仿真实验验证了所提动态参数辨识方法与控制算法的有效性，实验结果表明该方案的综合应用可有效提升机器人的控制性能。