锻压技术

基于小波神经网络控制的伺服直驱泵控系统压力与位置特性分析

英文标题：Analysis on pressure and position characteristics of servo direct drive pump-control-cylinder system based on wavelet neural network control

作者：韩贺永乔永杰刘少龙王凯

单位：太原科技大学

关键词：泵控缸系统小波神经网络 AMEsim Simulink 双闭环控制联合仿真

分类号：TH137

出版年,卷(期):页码：2018,43(2):0-0

摘要：

由于伺服直驱泵控缸压力与位置双闭环控制系统的结构复杂，存在非线性、时变性等特点，单纯通过数学模型进行分析比较繁琐，结果也不精确。通过对泵控缸压力与位置双闭环控制工作原理的分析，在AMEsim中搭建出系统控制回路的物理模型，在Simulink中搭建小波神经网络控制部分模型，然后进行联合仿真分析，并进行实验验证。伺服电机采用三相交流永磁同步电机，控制芯片采用DSP28335，驱动器采用台达ASDA-A2伺服驱动器，实验采用2种控制方式，即普通PID控制和小波神经网络控制，通过对额定负载情况下压力与位置的响应特性曲线进行分析，结果表明采用小波神经网络控制可以显著提高伺服直驱泵控缸压力与位置控制系统的控制精度和稳定性。

Because the double closed-loop control system structure of pressure and position for servo direct drive pump-control-cylinder are complex, nonlinear and time-invariance, the analysis solely based on mathematical model will be very complicate with inaccurate result. By analyzing the double closed-loop control principle of pressure and position for pump-control-cylinder, a physical model of the system control loop was set up by AMEsim, and the wavelet neural network control model was constructed by Simulink. Then, the co-simulation analysis was conducted, and the experimentation and verification were also performed. Therefore, three-phase AC permanent magnet synchronous motor was used as the servo motor, DSP28335 was used as the control chip, and the telda ASDA-A2 servo drive was used as the drive. The experiment was controlled by both common PID control and wavelet neural network control, and the response characteristics curves of pressure and position under rated load were analyzed. The results show that the control precision and stability of control system for servo direct drive pump-control-cylinder system can be improved significantly by the wavelet neural network control.

基金项目：

国家自然科学基金资助项目（51505315）

作者简介：韩贺永（1982－)，男，博士，副教授 E-mail：277921887@qq.com

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