摘要
本文通过详细介绍BP神经网络PID控制算法,并且针对油气井井下机器人的调速系统\进行分析研究,分别针对神经网络PID控制和传统的PID控制进行比较比较和选择,然后选择合理电机参数对油气井井下机器人的转速调节过程进行Matlab算法模拟与仿真。
This article introduces the proportion integration differentiation(PID) algorithm based on back propagation(BP)neural network.The speed governor of the robot is described as well.The conventional and neural network PID control are compared to select the optimal parameters of the electric machines for simulation of the speed adjustment of the robot via Madab algorithm.
出处
《石化技术》
CAS
2016年第10期140-141,共2页
Petrochemical Industry Technology
关键词
PID控制
油气井
井下机器人
神经网络
仿真
proportion integration differentiation control
oil and gas well
down-hole robot
neural network
simulation
