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广义模糊聚类及其在T-S模型辨识中的应用
肖颻
Subtype工学硕士
Thesis Advisor高东杰
2001-05-01
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
KeywordT-s模型 模糊聚类 G-k方法 Afc方法 系统辨识 T-s Model Identification Fuzzy Clustering G-k Fcm Afc
Abstract模糊聚类经过几十年的发展,已经成为一种非常常用的工具。而对 于模糊聚类本身的探讨,也是研究的热点问题之一。本文主要侧重于它在控制领域中的应用,尤其在T-S模糊模型辨识中的应用。 本文主要分两大部分:模糊聚类和它在T-S模型辨识中的应用。 在第一部分中,首先介绍了模糊聚类的研究背景和最常用的几种聚 类方法。然后提出了广义的聚类方法。并说明了G-K和AFC都是同一 方法的不同动态参数选择的结果。最后,对广义聚类方法中的动态参数 的选择方法进行了实验和讨论。证明原来AFC参数选择的不合理。 在第二部分中,先对T-S模型和系统辨识做了比较详细的介绍, 然后对广义的聚类方法进一步改进,提出了对T-S辨识中的聚类原型应 该由点变成线性。在隶属度函数中选择了钟型函数,讨论了它的特点。 在两个仿真实验中证明了该方法的优点。
Other AbstractThe fuzzy clustering is an important branch of pattern recognition and control theory. Many algorithms have been presented as a result of its widespread application. In this thesis, we focus on a new general fuzzy clustering and its application for T-S model identification. The article was originated as following: the section one was the brief introduction on fuzzy clustering techniques. Also, some common algorithms were presented, such as HCM, FCM and G-K. In the section 2na, we give a detailed Mahanna distance measurement, compared with Eulide distance, it has more desirous characters. Based on the compartments, a new general fuzzy clustering was attended. And the section 3rd included some tests on the new fuzzy clustering method. The T-S model and its identification were the 4th part of the article. And in the last section, section 5t~, the general fuzzy clustering was further extended. The adjusting of clustering prototype brought the algorithm some new attractive characters. Also two experiments were done to show the validity of the new fuzzy clustering in system identification. Besides that, some results from the experiments prove that there was un-proper choice of the parameter in original AFC method, and the belly shape membership was explored.
shelfnumXWLW602
Other Identifier602
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6857
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
肖颻. 广义模糊聚类及其在T-S模型辨识中的应用[D]. 中国科学院自动化研究所. 中国科学院研究生院,2001.
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