| 引用本文: | 刘福才,吕金凤,任亚雪.考虑重要输入变量选择的非线性系统模糊辨识[J].控制理论与应用,2021,38(9):1381~1392.[点击复制] |
| LIU Fu-cai,LV Jin-feng,REN Ya-xue.Fuzzy identification of nonlinear system considering the selection of important input variables[J].Control Theory and Technology,2021,38(9):1381~1392.[点击复制] |
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| 考虑重要输入变量选择的非线性系统模糊辨识 |
| Fuzzy identification of nonlinear system considering the selection of important input variables |
| 摘要点击 1550 全文点击 522 投稿时间：2020-10-12 修订日期：2021-03-22 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2021.00686 |
| 2021,38(9):1381-1392 |
| 中文关键词 模糊系统 输入变量选择 Takagi-Sugeno(T–S)模型 模糊聚类(FCM)算法 Gaussian函数 气动加载系统 |
| 英文关键词 fuzzy systems input variable selection Takagi-Sugeno (T–S) model fuzzy C–means (FCM) algorithm Gaussian function pneumatic loading system |
| 基金项目 载人航天领域预研项目(2016040301), 河北省自然科学基金项目(F2019203505)资助. |
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| 中文摘要 |
| 针对有数百个可能输入的复杂非线性动态系统模糊建模问题, 本文提出一种新的考虑重要输入变量选择
的模糊辨识方法. 首先采用两阶段模糊曲线方法(TSFC)从大量可选择的输入变量中给出各输入变量与输出之间的
关联度权重, 根据输入变量指标快速选择出重要的输入变量, 然后采用模糊聚类(FCM)和高斯(Gaussian)型隶属函
数确定模糊模型前提参数, 采用递推最小二乘(RLS)辨识出模糊模型结论参数. 最后通过对Mackey-Glass混沌时间
序列和Box-Jenkins煤气炉数据两个国际标准例题模糊建模验证了该方法的有效性, 并将该方法应用到一个实际气
动变载荷加载系统的模糊建模中, 验证了该方法的实用性. |
| 英文摘要 |
| Aiming at the fuzzy modeling of complex nonlinear dynamic systems with hundreds of possible inputs, this
paper proposes a new fuzzy identification method considering the selection of important input variables. First, the two
stage fuzzy curves method (TSFC) is used to give the weight of the correlation between each input variable and the output
from a large number of selectable input variables, and the important input variable is quickly selected according to the
input variable index. Then fuzzy C–means clustering (FCM) and Gaussian membership functions are used to determine the
premise parameters of the fuzzy model, and recursive least squares (RLS) are used to identify the conclusion parameters
of the fuzzy model. Finally, the effectiveness of the method is verified by fuzzy modeling of two international standard
examples of Mackey-Glass Chaotic System and Box-Jenkins system. In order to verify the practicability of this method,
this method is applied to the fuzzy modeling of an actual variable load pneumatic loading system. |