基于双观测器的机器人自适应摩擦补偿控制

针对机器人系统中存在关节摩擦的问题，提出一种基于终端滑模观测器和摩擦状态观测器的双观测器自适应摩擦补偿反演控制方案:为避免速度测量带来的噪声影响，设计终端滑模观测器对机器人的速度进行估计；考虑到摩擦力无法直接获取，采用连续LuGre摩擦模型，设计摩擦状态观测器和摩擦参数自适应律，得到摩擦的估计值；结合摩擦估计值设计反演控制器，使机器人在受到关节摩擦影响的情况下能有效跟踪期望位置轨迹。最后通过Lyapunov函数证明闭环系统的稳定性以及机器人轨迹跟踪误差的收敛性，并通过MATLAB仿真验证该控制方案的有效性。仿真结果表明，该控制方法能有效抑制关节摩擦对机器人轨迹跟踪的影响，提高了系统的位置跟踪精度。

Adaptive Friction Compensation Control for Robot Based on Dual-observer

For the influence of joint friction in robotic system, a dual-observer adaptive backstepping control scheme based on terminal sliding mode observer and friction state observer was proposed in this paper. Firstly, in order to avoid the influence of noise caused by velocity measurement, a terminal sliding mode observer was designed to estimate the velocity of the robot. Then, considering that friction could not be obtained directly, a continuous LuGre friction model was used to design the friction state observer and the adaptive law of friction parameters to get an estimation of the friction. Finally, a backstepping controller was designed based on the estimation value of the friction, so that the robot can effectively track the desired position trajectory under the influence of joint friction. The stability of the closed-loop system and the convergence of position error for the robot were proved with Lyapunov function. The effectiveness of the proposed control scheme was verified with MATLAB simulations. The results showed that the proposed control method can effectively suppress the influence of friction on the position tracking of the robot and improve the position tracking accuracy of the system.