昝鹏, 颜国正, 于莲芝. 基于神经网络PID控制的柔性微机器人系统[J]. 机器人, 2007, 29(3): 219-223,229.
引用本文: 昝鹏, 颜国正, 于莲芝. 基于神经网络PID控制的柔性微机器人系统[J]. 机器人, 2007, 29(3): 219-223,229.
ZAN Peng, YAN Guo-zheng, YU Lian-zhi. A Flexible Miniature Robotic System Based on Neural Network PID Control[J]. ROBOT, 2007, 29(3): 219-223,229.
Citation: ZAN Peng, YAN Guo-zheng, YU Lian-zhi. A Flexible Miniature Robotic System Based on Neural Network PID Control[J]. ROBOT, 2007, 29(3): 219-223,229.

基于神经网络PID控制的柔性微机器人系统

A Flexible Miniature Robotic System Based on Neural Network PID Control

  • 摘要: 根据尺蠖蠕动的原理,研制了一种三自由度微型机器人内窥镜诊疗系统;该机器人由空气压橡胶驱动器驱动,通过两个气囊钳位.建立了机器人的动态模型.基于BP神经网络PID控制策略,设计了电—气脉宽调制伺服系统控制机器人的移动.用系统输出的预测值来代替实测值,计算权系数的修正量,实时改变控制参数以提高控制效果.软件仿真和实验结果都证实该方法弥补了传统PID控制方法的不足,显著改善了系统的静动态特性,是一种理想的气动微型蠕动机器人控制方法.

     

    Abstract: Based on inchworm locomotion principle,a 3-DOF miniature endoscopic inspection squirming robot system is designed,which is driven by a pneumatic rubber actuator and clamped by two air chambers.Dynamic model of the robot is built.With BP neural network PID scheme,an electro-pneumatic PWM(Pulse-Width Modulation)servo controller is designed to control the robot movement.With the predicted value of system output instead of measured value,the weight co-effient is corrected and the controller parameters are changed in real time to improve the control performance.Both simulation and experimental results indicate that this scheme can overcome the shortages of traditional PID controllers,improve the system static and dynamic performance,and is an ideal control method for pneumatic miniature squirming robots.

     

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