Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression

Xianxia Zhang; Ye Jiang; Tao Zou; Chenkun Qi; Guitao Cao

doi:10.1109/FUZZY.2011.6007684

Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression

Xianxia Zhang^*
, Ye Jiang
, Tao Zou
, Chenkun Qi
, Guitao Cao

^*Corresponding author for this work

Software Engineering Institute

Shanghai University
Zhejiang University of Technology
Shanghai Jiao Tong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Three-dimensional fuzzy logic controller (3-D FLC) is a novel FLC developed for spatially distributed parameter systems. In this study, we are concerned with data-based 3-D FLC design. A nearest neighborhood clustering algorithm is employed to extract fuzzy rules from input-output data pairs, and then an optimization algorithm based on geometric similarity measure is used to reduce the obtained rule base. The consequent parameters are estimated using linear support vector regression. Finally, a catalytic packed-bed reactor is taken as an application to demonstrate the effectiveness of the 3-D FLC.

Original language	English
Title of host publication	FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	374-380
Number of pages	7
ISBN (Print)	9781424473175
DOIs	https://doi.org/10.1109/FUZZY.2011.6007684
State	Published - 2011

Publication series

Name	IEEE International Conference on Fuzzy Systems
ISSN (Print)	1098-7584

Keywords

3-D fuzzy set
linear support vector regression
nearest neighborhood clustering
three-dimensional fuzzy logic controller

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10.1109/FUZZY.2011.6007684

Cite this

Zhang, X., Jiang, Y., Zou, T., Qi, C., & Cao, G. (2011). Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression. In FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 374-380). Article 6007684 (IEEE International Conference on Fuzzy Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZY.2011.6007684

Zhang, Xianxia ; Jiang, Ye ; Zou, Tao et al. / Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression. FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2011. pp. 374-380 (IEEE International Conference on Fuzzy Systems).

@inproceedings{74a8ecf785d14a3dac84822cab7c2b75,

title = "Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression",

abstract = "Three-dimensional fuzzy logic controller (3-D FLC) is a novel FLC developed for spatially distributed parameter systems. In this study, we are concerned with data-based 3-D FLC design. A nearest neighborhood clustering algorithm is employed to extract fuzzy rules from input-output data pairs, and then an optimization algorithm based on geometric similarity measure is used to reduce the obtained rule base. The consequent parameters are estimated using linear support vector regression. Finally, a catalytic packed-bed reactor is taken as an application to demonstrate the effectiveness of the 3-D FLC.",

keywords = "3-D fuzzy set, linear support vector regression, nearest neighborhood clustering, three-dimensional fuzzy logic controller",

author = "Xianxia Zhang and Ye Jiang and Tao Zou and Chenkun Qi and Guitao Cao",

year = "2011",

doi = "10.1109/FUZZY.2011.6007684",

language = "英语",

isbn = "9781424473175",

series = "IEEE International Conference on Fuzzy Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "374--380",

booktitle = "FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings",

address = "美国",

}

Zhang, X, Jiang, Y, Zou, T, Qi, C & Cao, G 2011, Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression. in FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings., 6007684, IEEE International Conference on Fuzzy Systems, Institute of Electrical and Electronics Engineers Inc., pp. 374-380. https://doi.org/10.1109/FUZZY.2011.6007684

Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression. / Zhang, Xianxia; Jiang, Ye; Zou, Tao et al.
FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2011. p. 374-380 6007684 (IEEE International Conference on Fuzzy Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression

AU - Zhang, Xianxia

AU - Jiang, Ye

AU - Zou, Tao

AU - Qi, Chenkun

AU - Cao, Guitao

PY - 2011

Y1 - 2011

N2 - Three-dimensional fuzzy logic controller (3-D FLC) is a novel FLC developed for spatially distributed parameter systems. In this study, we are concerned with data-based 3-D FLC design. A nearest neighborhood clustering algorithm is employed to extract fuzzy rules from input-output data pairs, and then an optimization algorithm based on geometric similarity measure is used to reduce the obtained rule base. The consequent parameters are estimated using linear support vector regression. Finally, a catalytic packed-bed reactor is taken as an application to demonstrate the effectiveness of the 3-D FLC.

AB - Three-dimensional fuzzy logic controller (3-D FLC) is a novel FLC developed for spatially distributed parameter systems. In this study, we are concerned with data-based 3-D FLC design. A nearest neighborhood clustering algorithm is employed to extract fuzzy rules from input-output data pairs, and then an optimization algorithm based on geometric similarity measure is used to reduce the obtained rule base. The consequent parameters are estimated using linear support vector regression. Finally, a catalytic packed-bed reactor is taken as an application to demonstrate the effectiveness of the 3-D FLC.

KW - 3-D fuzzy set

KW - linear support vector regression

KW - nearest neighborhood clustering

KW - three-dimensional fuzzy logic controller

UR - https://www.scopus.com/pages/publications/80053062990

U2 - 10.1109/FUZZY.2011.6007684

DO - 10.1109/FUZZY.2011.6007684

M3 - 会议稿件

AN - SCOPUS:80053062990

SN - 9781424473175

T3 - IEEE International Conference on Fuzzy Systems

SP - 374

EP - 380

BT - FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Zhang X, Jiang Y, Zou T, Qi C, Cao G. Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression. In FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2011. p. 374-380. 6007684. (IEEE International Conference on Fuzzy Systems). doi: 10.1109/FUZZY.2011.6007684

Data-driven based 3-D fuzzy logic controller design using nearest neighborhood clustering and linear support vector regression

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