基于改进的引力搜索算法的T-S模型辨识

›› 2015, Vol. 28 ›› Issue (11): 16-.

基于改进的引力搜索算法的T-S模型辨识

董新燕,丁学明,王健

(上海理工大学光电信息与计算机工程学院,上海 200093)

出版日期:2015-11-15 发布日期:2015-12-15
作者简介:董新燕(1990—),女,硕士研究生。研究方向:系统辨识,智能控制。E-mail:1163574752@qq.com
基金资助:
沪江基金资助项目(A14001,B1402,D1402)

T S Model Identification Based on an Improved Gravitational Search Algorithm

DONG Xinyan,DING Xueming,WANG Jian

(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

Online:2015-11-15 Published:2015-12-15

摘要/Abstract

摘要：

针对引力搜索算法在求解复杂问题时搜索精度较低、易出现早熟收敛的缺点。提出一个新颖的智能算法-基于基因突变的引力搜索算法来辨识T-S模型的参数,同时提出一种改进的聚类算法辨识T-S模型的结构,实验结果表明,改进算法辨识出的T-S模型结构紧凑、精度更高,且泛化能力强。

关键词: T S模型辨识, 基因突变, FCM聚类, 引力搜索算法

Abstract:

As the gravitational search algorithm plays a negative influence on the search accuracy of the complex issues,especially the poor search quality of standard Gravitational Search Algorithm(GSA) in the high dimensional function optimization,it is easy to get into premature convergence in the optimization process.An improved gravitational search algorithm based on genetic mutations(gmGSA) is proposed to identify the parameter of T-S model.An improved fuzzy c-means(FCM) based on simulated annealing(SA) and genetic algorithm(GA),denote as SAGA-FCM,is also proposed to identify the structure of T-S model.The simulation results show the proposed methods can effectively obtain compact and accurate fuzzy models with excellent capability of generalization.

Key words: identification of T S model;genetic mutations;FCM clustering;gravitational search algorithm

中图分类号:

TP273.4

董新燕,丁学明,王健. 基于改进的引力搜索算法的T-S模型辨识[J]. , 2015, 28(11): 16-.

DONG Xinyan,DING Xueming,WANG Jian. T S Model Identification Based on an Improved Gravitational Search Algorithm[J]. , 2015, 28(11): 16-.

[1]	汤依婷，韩彦芳. 一种改进的图割目标分割算法[J]. , 2016, 29(10): 43-.
[2]	董新燕,丁学明,王健. 基于改进的引力搜索算法的T-S模型辨识[J]. , 2015, 27(11): 16-.