Multi-Inverse Model Switching Control for Valve-Controlled Asymmetric Cylinder Systems Based on Neural Network

doi:10.7652/xjtuxb201912020

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Multi-Inverse Model Switching Control for Valve-Controlled Asymmetric Cylinder Systems Based on Neural Network

更新时间：2025-07-09

- Multi-Inverse Model Switching Control for Valve-Controlled Asymmetric Cylinder Systems Based on Neural Network
- Vol. 53, Issue 12, Pages: 153-160(2019)
- 作者机构：
  
  1. 中南大学机电工程学院高性能复杂制造国家重点实验室,长沙,410083
  2. 长沙航空职业技术学院航空机械制造系,长沙,410124
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201912020
  CLC： TP273
- Online First：10 December 2019，
  
  Published：2019
- 稿件说明：
移动端阅览
Multi-Inverse Model Switching Control for Valve-Controlled Asymmetric Cylinder Systems Based on Neural Network[J]. 2019, 53(12): 153-160.
DOI：

Multi-Inverse Model Switching Control for Valve-Controlled Asymmetric Cylinder Systems Based on Neural Network[J]. 2019, 53(12): 153-160. DOI： 10.7652/xjtuxb201912020.

摘要

为提高存在负叠合量的阀控非对称缸系统的控制性能

提出基于神经网络的逆系统控制方法

利用神经网络逼近的逆模型与原系统复合

将复杂非线性系统转变为线性系统进行控制

建立了阀控非对称缸系统的数学模型

系统在(x

u)的邻域内存在相对阶

证明了系统的可逆性; 采用基于遗传算法改进的BP神经网络(GA-BP)求解逆模型

并针对伺服阀存在负叠合量

以及流态存在层流和紊流两种状态的问题

建立系统的多个逆模型集

提高了逆系统的求解精度。利用AMESIM和Simulink联合仿真平台

基于参考速度切换的原则

对系统采用比例-积分-微分(PID)闭环控制器。结果表明:普通PID控制的液压缸伸出运动响应和缩回运动响应不一致

伸出运动存在0.20 mm的稳态误差

误差波动范围为0.06 mm

而缩回运动稳态误差较小

约为0.02 mm

但误差波动较大

约为0.09 mm; 多逆系统复合控制的伸出缩回运动响应较一致

伸出和缩回运动均存在0.02 mm的稳态误差

误差波动范围为0.04 mm

验证了多逆模型切换控制方法可以消除阀控非对称缸系统的非对称性

降低波动负载干扰影响

提高系统的响应精度。

Abstract

A control method based on a neural network inverse system is proposed to improve the control performance of valve-controlled asymmetric cylinder systems with negative overlap. An inverse model of neural network approximation is used to transform the complex nonlinear system into a linear system. A mathematical model is established for the valve-controlled asymmetric cylinder system

and the system exists relative orders in the neighborhood of (x

which proves the reversibility of the system. An improved BP neural network based on a genetic algorithm(GA-BP)is used to so

lve the inverse model. Aiming at the problems of the negative overlap and the laminar and turbulent flow in the servo valve

several inverse models for the system are established to improve the accuracy of the inverse system. Finally

a simulation platform combined with AMESIM and Simulink is used

and a proportional-integral-derivative(PID)closed-loop controller is adopted for the system based on the princ

关键词

Keywords

references

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