摘要
对一类石油化工生产过程中的Wiener模型辨识问题,提出了一种稳态与动态相结合的集成辨识方法.利用稳态信息获取稳态模型的强一致性估计,通过神经网络逼近得到非线性增益的逆函数.然后利用系统的动态信息辨识Wiener模型的线性系统的参数,并得到一致性估计.仿真结果表明了该方法的有效性和实用性.
In accordance with a class of Wiener model in petroleum chemical engineering,an
identification method for Wiener model is put forward.In this method,the steadystate model a
system is obtained from its steadystate data.The inverse function of nonlinear gain is get by
using neural network.The nonlinearity of the system can be eliminated by the inverse
function,so Wiener model becomes a pure linear model.The linear parameters of the model can
be gained according to the dynamic data of the system.The effectiveness and practicality of this
method is demonstrated by the simulation results of examples.
出处
《西安石油学院学报(自然科学版)》
1999年第4期68-69,共2页
Journal of Xi'an Petroleum Institute(Natural Science Edition)
基金
国家自然科学基金
关键词
数学型
非线性
模式识别
集成辨识
W模型
mathematical model,
nonlinearity,pattern recognition,nerve network,Wiener model,integrated identification