LAPSE:2023.4793
Published Article

LAPSE:2023.4793
Deep Hierarchical Interval Type 2 Self-Organizing Fuzzy System for Data-Driven Robot Control
February 23, 2023
Abstract
To solve the dimensional explosion problem, this paper proposes a new architecture for the fuzzy system, the deep hierarchical self-organizing interval type-2 fuzzy system (DHSOIT2FS). Each sub-fuzzy system is a self-organizing interval type-2 fuzzy system, constructed online, with rules constructed by a rule online update algorithm, consequent parameters updated by iterative least squares, and antecedent parameters are updated using a gradient descent algorithm. DHSOIT2FS uses a classic serial-layered structure to build the overall framework. The first layer uses the first two dimensions of data as input. Each subsequent layer uses the output of the previous layer with the next dimensional data as input until it is built. During the training process, each data point is trained with DHSOIT2FS before passing in the next data point to achieve online construction. The effectiveness of the approach in this paper is illustrated using two numerical simulation examples. The proposed method is also applied to a data-driven control example of a single-link robot and achieves good tracking results.
To solve the dimensional explosion problem, this paper proposes a new architecture for the fuzzy system, the deep hierarchical self-organizing interval type-2 fuzzy system (DHSOIT2FS). Each sub-fuzzy system is a self-organizing interval type-2 fuzzy system, constructed online, with rules constructed by a rule online update algorithm, consequent parameters updated by iterative least squares, and antecedent parameters are updated using a gradient descent algorithm. DHSOIT2FS uses a classic serial-layered structure to build the overall framework. The first layer uses the first two dimensions of data as input. Each subsequent layer uses the output of the previous layer with the next dimensional data as input until it is built. During the training process, each data point is trained with DHSOIT2FS before passing in the next data point to achieve online construction. The effectiveness of the approach in this paper is illustrated using two numerical simulation examples. The proposed method is also applied to a data-driven control example of a single-link robot and achieves good tracking results.
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Keywords
data-driven robot control, interval type-2 fuzzy system, self-organizing fuzzy system
Subject
Suggested Citation
Mei Z, Zhao T, Liu N. Deep Hierarchical Interval Type 2 Self-Organizing Fuzzy System for Data-Driven Robot Control. (2023). LAPSE:2023.4793
Author Affiliations
Mei Z: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Zhao T: College of Electrical Engineering, Sichuan University, Chengdu 610065, China [ORCID]
Liu N: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Zhao T: College of Electrical Engineering, Sichuan University, Chengdu 610065, China [ORCID]
Liu N: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Journal Name
Processes
Volume
10
Issue
10
First Page
2091
Year
2022
Publication Date
2022-10-15
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr10102091, Publication Type: Journal Article
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LAPSE:2023.4793
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https://doi.org/10.3390/pr10102091
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Feb 23, 2023
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