具有不确定性的主从机械手自适应模糊控制

针对具有不确定性且存在执行器未知约束的遥操作机器人系统，研究自适应模糊轨迹跟踪控制方案。该方案无需精确建立机器人遥操作系统的动力学模型，也不需要测量机械臂末端的运动参数与末端受到的外力。通过自适应模糊系统逼近未知的机器人动力学模型，利用运动学参数线性化特性构建预估机器人雅可比矩阵，辅以参数更新律实现跟踪目标的近似表示。此外，通过采用Nussbaum函数处理执行器受到的输入约束实现输入约束补偿。针对遥操作机器人系统主从端受到的相互作用力，借助自适应模糊系统，在控制律中添加模糊项实现对相互作用力的逼近，从而实现更为稳定、精确的轨迹跟踪。通过李亚普诺夫稳定性理论证明了闭环动力学系统是有界的，且位置误差收敛于零，仿真试验进一步证明了理论方案的有效性。

Adaptive Fuzzy Control for Master-Slave Manipulators with Uncertainties

An adaptive fuzzy trajectory tracking control scheme was studied for a class of teleoperated robot systems with dynamics, kinematic uncertainties and unknown constraints of actuators. In the scheme,accurate dynamics model of the robot remote operating system was not needed,the motion parameters of the end of the manipulator and the external force on the end were unnecessary to measure.The unknown robot dynamics model was approximated by an adaptive fuzzy system, the Jacobian matrix of the predicted robot was constructed by using the linearization characteristics of the kinematic parameters, and the approximate representation of the tracking target was realized with the help of parameter update law.In addition, an adaptive fuzzy online trajectory tracking control law was designed by using Nussbaum function to process the input constraints of the actuator to realize input constraint compensation. Aiming at the interaction force received by the master and slave end of the teleoperation robot system, with the help of the adaptive fuzzy system, the fuzzy terms were added to the control law to achieve the approximation of the interaction force, so as to achieve more stable and accurate trajectory tracking.It is proved that all the closed-loop signals are bounded and the position error converges to zero. The simulation test further proves the effectiveness of the theoretical scheme.