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基于神经网络控制算法的气动伺服系统运动分析研究
引用本文:许翔宇,袁锐波.基于神经网络控制算法的气动伺服系统运动分析研究[J].机械与电子,2016,0(8):41-43,47.
作者姓名:许翔宇  袁锐波
作者单位:(昆明理工大学机电工程学院 云南 昆明 650500)
摘    要:提出了一种神经网络控制方法并通过对气动伺服系统的无杆气缸运动控制,探究此控制方法的控制精度。由于受空气可压缩性、摩擦力以及启动系统的扰动等非线性因素的影响,气动伺服系统很难去建立精确的数学模型。根据系统的非线性特点及PID控制不足,基于BP神经网络控制,设计神经网络PID控制器,并进行实验。通过实验,对无杆气缸的运动特性分析,表明这种控制策略可以更好控制气动伺服系统的运动精度。

关 键 词:气动伺服系统  神经网络控制  运动精度

Motion Analysis for the Pneumatic Servo System based on the Neural Network Control Algorithm
XU Xiangyu,YUANG Ruibo.Motion Analysis for the Pneumatic Servo System based on the Neural Network Control Algorithm[J].Machinery & Electronics,2016,0(8):41-43,47.
Authors:XU Xiangyu  YUANG Ruibo
Affiliation:(Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering,Kunming 650500,China)
Abstract:This paper presents a neural network control method and explores the control accuracy of this control method through control of the rod-free cylinder motion of the pneumatic servo system. It is difficult to establish an accurate mathematical modelfor the pneumatic servo system due to the influence of the nonlinear factors such as the compressibility of the air, the friction force and the disturbance of the starting system. In this paper, based on the nonlinear characteristics of the system and the PID control problem and the BP neural network control, a neural network PID controller is designed and tested. The analysis of the motion characteristics of the rod-free cylinder shows that the control strategy can better control the motion accuracy of the pneumatic servo system.
Keywords:pneumatic servo system  neural network control  motion precision
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