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基于小波神经网络的板形板厚综合系统逆控制
引用本文:黄敏,崔宝同,顾树生.基于小波神经网络的板形板厚综合系统逆控制[J].控制与决策,2007,22(5):593-596.
作者姓名:黄敏  崔宝同  顾树生
作者单位:1. 江南大学,控制科学与工程研究中心,江苏,无锡,214122
2. 东北大学,信息科学与工程学院,沈阳,110004
基金项目:国家自然科学基金项目(60274024).
摘    要:针对板形板厚综合系统具有强耦合、非线性、含纯滞后环节的特点,提出一种基于小波神经网络的逆控制方案.利用两个结构相同的小波神经网络构造Smith预估器,预估器的输入参数与时延阶次无关,能较好地解决小波神经网络对维数较为敏感的问题.采用神经网络逆控制的思想设计小波神经网络控制器,引入多步预测性能指标函数对控制器权值进行在线训练.仿真研究表明,该控制方案具有较快的响应速度和良好的动态性能.

关 键 词:小波神经网络  板形控制  板厚控制  逆控制
文章编号:1001-0920(2007)05-0593-04
收稿时间:2006/2/9 0:00:00
修稿时间:2006-02-092006-06-09

Strip flatness and gauge inverse control based on wavelet neural networks
HUANG Min,CUI Bao-tong,GU Shu-sheng.Strip flatness and gauge inverse control based on wavelet neural networks[J].Control and Decision,2007,22(5):593-596.
Authors:HUANG Min  CUI Bao-tong  GU Shu-sheng
Affiliation:1. Research Center of Control Science and Engineering, Southern Yangtze University, Wuxi 214122, China; 2. College of Information Science and Engineering, Northeastern University, Shenyang 110004, China
Abstract:The process of automatic flatness control and automatic gauge control(AFC-AGC) is a nonlinear system with strong coupling and pure time delay.An inverse control method of AFC-AGC is developed,in which Smith predictor is designed by using two wavelet neural networks(WNN) whose structures and parameters are identical.Because inputs of network are independent of time delay order,the sensitivity of dimension for WNN is reduced.A WNN controller with the idea of neural networks inverse control is applied.Using multi-step predictive index function to train the weights of controller.Simulation results show that the system has better response performance.
Keywords:Wavelet neural networks  Flatness control  Gauge control  Inverse control
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