绳索牵引式并联机器人神经网络PID控制

Neural network PID control of cable-towed parallel robot

分析了一种6绳索6自由度的绳索牵引式并联机器人,基于齐次变换矩阵法建立了机器人运动学和动力学模型,根据其动力学模型及传统PID控制器,基于BP神经网络设计了BP神经网络PID控制器,机器人在运动过程中通过BP神经网络调整PID参数。最后通过仿真将其控制结果与基于传统PID控制器的控制结果进行对比,得出这种控制方法能够提高绳索牵引式并联机器人的控制精度和响应速度。

A kinematic and dynamic model of a six-cable 6-DOF cable-towed parallel robot is built based on the homogeneous transformation matrix method. According to the dynamic model traditional PID controller, a BP neural network PID controller is designed, and the controller adjusts the PID parameters through BP neural network during the movement of the robot. At last, after comparing the simulation of the control result with the control result based on the traditional PID controller, it can be concluded that the proposed control method can improve the control accuracy and response of the cable-towed parallel robot.