Matching localization algorithm of nonlinear T–S fuzzy system constructed by the piecewise linear function

The piecewise linear function is a generalization of a segmentation linear functions with one variable in the multivariate case, which is an important tool to describe the relationships between fuzzy system and approximation function. Firstly, aiming at the μ ^ -integrable function, the concrete met...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of ambient intelligence and humanized computing Ročník 10; číslo 2; s. 417 - 427
Hlavní autoři: Wang, Guijun, Zhang, Guoying
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2019
Springer Nature B.V
Témata:
Algorithms
Approximation
Artificial Intelligence
Computational Intelligence
Engineering
Fuzzy logic
Fuzzy sets
Fuzzy systems
Linear functions
Localization
Matching
Mathematical functions
Mathematical models
Original Research
Robotics and Automation
User Interfaces and Human Computer Interaction
Piecewise linear function
Singleton fuzzifier
Nonlinear T–S fuzzy system
integrable function
Matching-localization algorithm
ISSN:1868-5137, 1868-5145
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The piecewise linear function is a generalization of a segmentation linear functions with one variable in the multivariate case, which is an important tool to describe the relationships between fuzzy system and approximation function. Firstly, aiming at the μ ^ -integrable function, the concrete method of constructing piecewise linear functions and their analytical expressions were introduced, furthermore, based on the piecewise linear functions, we constructed the nonlinear T–S fuzzy systems with a singleton fuzzifier in this paper. And then, we put forward the matching-localization algorithm of the fuzzy system based on the spatial positioning mode for the input variables in the domain. Finally, the effectiveness of the matching localization algorithm of the nonlinear T–S fuzzy system was verified by the means of the simulation example. The results show that the approximating ability of the fuzzy system to a μ ^ -integrable function can be adjusted by changing the subdivision parameters.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-017-0556-7