机器人系统摩擦力矩和摩擦模型参数自适应有限时间估计与仿真

Adaptive Finite-Time Estimation and Simulation of Friction Torque and Friction Model Parameters of Robot Systems

针对机器人系统中存在非线性摩擦影响控制系统性能的问题,文中提出一种自适应参数估计算法对一类连续摩擦模型的关键参数进行辨识,实现摩擦建模。为避免使用加速度信号,需对机器人系统模型进行重构并设计未知系统动态估计器来实现摩擦力矩的整体估计。该估计器结构简单,仅需调节一个参数即可实现对摩擦力矩的估计,且估计的收敛速度快,有利于在实际系统中实现。在获得摩擦力矩估计的基础上,基于李雅普诺夫方法构建基于参数估计误差信息的有限时间自适应参数估计算法。在保证算法收敛性和鲁棒性的前提下,可在有限时间内准确辨识连续摩擦模型中的关键参数。

The nonlinear friction torque in the robot system affects the performance of the control system.To address this problem,an adaptive parameter estimation algorithm is proposed to estimate the key parameters of a continuous friction model and realize the friction torque modeling.In order to avoid the use of acceleration signals,the robot system model is reconstructed and an unknown system dynamic estimator is designed to realize the overall estimation of the friction torque.The estimator has a simple structure,only needs to adjust one parameter to realize the estimation of the friction torque,and the estimated convergence speed is fast,which is beneficial to the realization in the actual system.On the basis of obtaining friction torque estimation,a finite-time adaptive parameter estimation algorithm based on parameter estimation error information is constructed according to the Lyapunov method.Under the premise of ensuring the convergence and robustness of the algorithm,the key parameters in the continuous friction model can be identified accurately in finite time.