Fuzzy Model Identification With Enhanced Validity Criterion for Mechanical System Design

CCUR > College of Natural Science and Engineering > College of Engineering > Department of Mechanical Engineering > journal articles > Item 987654321/22934

Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/22934

Title:	Fuzzy Model Identification With Enhanced Validity Criterion for Mechanical System Design
Authors:	Su, Kuo-Ho
Contributors:	機械工程學系
Keywords:	HYBRID ALGORITHM
Date:	2011-10
Issue Date:	2012-09-06 15:40:28 (UTC+8)
Abstract:	Model identification for machine system design, design optimization, and manufacturing planning is an important method that has high prediction accuracy and could become an essential stage in practical applications. In this paper, an effective fuzzy model identification algorithm for mechanical system design is developed. First, a fuzzy c-regression model clustering algorithm, in which hyperplane-shaped cluster representatives are utilized to provide a mathematical tool to partition the input-output space reasonably, is introduced. Then, an enhanced cluster validity criterion, in which the structural information hidden in the clusters can be reflected in the index, is proposed to choose the optimal number of clusters. In the proposed architecture, an improved Takagi-Sugeno fuzzy model is proposed to describe the system. Two illustrative examples under various conditions are provided, and their performances are indicated in comparison with other published works. In comparison to these fuzzy works, the proposed fuzzy model identification requires fewer fuzzy rules and a shorter tuning time. [DOI: 10.1115/1.4004483]
Relation:	JOURNAL OF MECHANICAL DESIGN Volume: 133 Issue: 10 Article Number: 104501
Appears in Collections:	[Department of Mechanical Engineering ] journal articles

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	563	View/Open

View Licence

Loading...