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一类非线性系统的模糊建模与仿真
引用本文:金梅,关学忠,金中石.一类非线性系统的模糊建模与仿真[J].系统仿真学报,2005,17(5):1030-1031,1047.
作者姓名:金梅  关学忠  金中石
作者单位:1. 大庆石油学院电气信息工程学院,黑龙江省大庆,163318
2. 大庆油田有限责任公司第二采油厂,黑龙江省大庆,163124
摘    要:将模糊推理建模法应用于一阶非线性系统,推导出基于该方法建模后得到的数学模型,即变系数线性微分方程。首先根据模糊逻辑系统的插值机理将被控对象的模糊推理规则库归结为某种线性插值函数,然后将这些插值函数转化为变系数线性微分方程,从而得到控制系统的数后将这些插值函数转化为变系数线性微分方程,从而得到控制系统的数学模型。仿真结果表明,用模糊推理建模法得到的模型关于真实模型具有较高的逼近精度。

关 键 词:模糊  推理建模  非线性系统  变系数  微分方程
文章编号:1004-731X(2005)05-1030-02

Fuzzy Modeling for a Nonlinear System
JIN Mei,GUAN Xue-zhong,JIN Zhong-shi.Fuzzy Modeling for a Nonlinear System[J].Journal of System Simulation,2005,17(5):1030-1031,1047.
Authors:JIN Mei  GUAN Xue-zhong  JIN Zhong-shi
Institution:JIN Mei1,GUAN Xue-zhong1,JIN Zhong-shi2
Abstract:The modeling method based on fuzzy inference is applied to first-order nonlinear system in this paper, and a mathematical model after modeling is deduced, that is, linear differential equation with variable coefficient. Firstly, according to interpolation mechanism on fuzzy logic system, fuzzy inference rule base is summed up to some interpolation function, then the function is transformed into differential equation with variable coefficient. Thus, a mathematical model is obtained. Simulation results show that the model formed by this method with regard to the real model has higher approaching precision.
Keywords:fuzzy  inference modeling  nonlinear system  variable coefficient  differential equation
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