An Applied Type-3 Fuzzy Logic System: Practical Matlab Simulink and M-Files for Robotic, Control, and Modeling Applications

被引：30

作者：

Huang, Haiyan ^{[1
]}

Xu, Hui ^{[2
]}

Chen, Fenghua ^{[1
]}

Zhang, Chunwei ^{[3
]}

Mohammadzadeh, Ardashir ^{[3
]}

机构：

[1] Zhejiang Guangsha Vocat & Tech Univ Construct, Sch Intelligent Mfg, Dongyang 322100, Peoples R China

[2] Jiangsu Huibo Robot Technol Co Ltd, Suzhou 215000, Peoples R China

[3] Shenyang Univ Technol, Multidisciplinary Ctr Infrastruct Engn, Shenyang 110870, Peoples R China

来源：

SYMMETRY-BASEL | 2023年 / 15卷 / 02期

关键词：

type-3 fuzzy systems; machine learning; artificial intelligence; interval type-2 fuzzy systems; general type-2 fuzzy systems; implementation; learning rules;

D O I：

10.3390/sym15020475

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In this paper, the main concepts of interval type-2 (IT2), generalized type-2 (GT2), and interval type-3 (IT3) fuzzy logic systems (FLSs) are mathematically and graphically studied. In representation approaches of fuzzy sets (FSs), the main differences between IT2, GT2, and IT3 fuzzy sets were investigated. For the first time, the simple Matlab Simulink and M-files by illustrative examples and symmetrical FSs are presented for the practical use of IT3-FLSs. The computations were simplified for the practical use of IT3-FLSs. By the use of various examples, such as online identification, offline time series modeling, and a robotic control system, the design of IT3-FLSs is elaborated. The required derivative equations are also presented to design the adaptation laws for the rule parameters easily in other learning schemes. Some simulation examples show that the designed M-files and Simulink work well and result in a good performance.

引用

页数：16

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