Intelligent Backstepping Control of Synchronous Reluctance Motor Drive System

Faa Jeng Lin; Shih Gang Chen; Che Wei Hsu

doi:10.1109/CACS.2018.8606767

Intelligent Backstepping Control of Synchronous Reluctance Motor Drive System

Faa Jeng Lin, Shih Gang Chen, Che Wei Hsu

Department of Electrical Engineering

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

3 Scopus citations

Abstract

An intelligent backstepping control (BSC) using recurrent feature selection fuzzy neural network (RFSFNN) is proposed to construct a high-performance synchronous reluctance motor (SRM) position drive system. First, the dynamics of the SRM position drive system and the BSC are briefly introduced. However, the lumped uncertainty of the SRM is unavailable to obtain in advance. Therefore, an intelligent backstepping control using recurrent feature selection fuzzy neural network (IBSCRFSFNN), which combines the advantages of recurrent neural network, fuzzy logic system and feature selection method, is developed to approximate an idea BSC and to maintain the stability of SRM position drive system. The network structure and online learning algorithm of the IBSCRFSFNN are described in detail. At last, the proposed control system is implemented in a floating-point TMS320F28075 digital signal processor. The experimental results are illustrated to show the validity of the proposed intelligent BSC system.

Original language	English
Title of host publication	2018 International Automatic Control Conference, CACS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538662786
DOIs	https://doi.org/10.1109/CACS.2018.8606767
State	Published - 2 Jul 2018
Event	2018 International Automatic Control Conference, CACS 2018 - Taoyuan, Taiwan Duration: 4 Nov 2018 → 7 Nov 2018

Publication series

Name	2018 International Automatic Control Conference, CACS 2018

Conference

Conference	2018 International Automatic Control Conference, CACS 2018
Country/Territory	Taiwan
City	Taoyuan
Period	4/11/18 → 7/11/18

Access to Document

10.1109/CACS.2018.8606767

Intelligent Control of Six-Phase Permanent Magnet Synchronous Motor Drive System for Electric Power Steering System(3/3)
Lin, F.-J. (PI)
1/08/17 → 31/07/18
Project: Research

Cite this

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title = "Intelligent Backstepping Control of Synchronous Reluctance Motor Drive System",

abstract = "An intelligent backstepping control (BSC) using recurrent feature selection fuzzy neural network (RFSFNN) is proposed to construct a high-performance synchronous reluctance motor (SRM) position drive system. First, the dynamics of the SRM position drive system and the BSC are briefly introduced. However, the lumped uncertainty of the SRM is unavailable to obtain in advance. Therefore, an intelligent backstepping control using recurrent feature selection fuzzy neural network (IBSCRFSFNN), which combines the advantages of recurrent neural network, fuzzy logic system and feature selection method, is developed to approximate an idea BSC and to maintain the stability of SRM position drive system. The network structure and online learning algorithm of the IBSCRFSFNN are described in detail. At last, the proposed control system is implemented in a floating-point TMS320F28075 digital signal processor. The experimental results are illustrated to show the validity of the proposed intelligent BSC system.",

author = "Lin, {Faa Jeng} and Chen, {Shih Gang} and Hsu, {Che Wei}",

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Lin, FJ, Chen, SG & Hsu, CW 2018, Intelligent Backstepping Control of Synchronous Reluctance Motor Drive System. in 2018 International Automatic Control Conference, CACS 2018., 8606767, 2018 International Automatic Control Conference, CACS 2018, Institute of Electrical and Electronics Engineers Inc., 2018 International Automatic Control Conference, CACS 2018, Taoyuan, Taiwan, 4/11/18. https://doi.org/10.1109/CACS.2018.8606767

Intelligent Backstepping Control of Synchronous Reluctance Motor Drive System. / Lin, Faa Jeng; Chen, Shih Gang; Hsu, Che Wei.
2018 International Automatic Control Conference, CACS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8606767 (2018 International Automatic Control Conference, CACS 2018).

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

TY - GEN

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AU - Lin, Faa Jeng

AU - Chen, Shih Gang

AU - Hsu, Che Wei

PY - 2018/7/2

Y1 - 2018/7/2

N2 - An intelligent backstepping control (BSC) using recurrent feature selection fuzzy neural network (RFSFNN) is proposed to construct a high-performance synchronous reluctance motor (SRM) position drive system. First, the dynamics of the SRM position drive system and the BSC are briefly introduced. However, the lumped uncertainty of the SRM is unavailable to obtain in advance. Therefore, an intelligent backstepping control using recurrent feature selection fuzzy neural network (IBSCRFSFNN), which combines the advantages of recurrent neural network, fuzzy logic system and feature selection method, is developed to approximate an idea BSC and to maintain the stability of SRM position drive system. The network structure and online learning algorithm of the IBSCRFSFNN are described in detail. At last, the proposed control system is implemented in a floating-point TMS320F28075 digital signal processor. The experimental results are illustrated to show the validity of the proposed intelligent BSC system.

AB - An intelligent backstepping control (BSC) using recurrent feature selection fuzzy neural network (RFSFNN) is proposed to construct a high-performance synchronous reluctance motor (SRM) position drive system. First, the dynamics of the SRM position drive system and the BSC are briefly introduced. However, the lumped uncertainty of the SRM is unavailable to obtain in advance. Therefore, an intelligent backstepping control using recurrent feature selection fuzzy neural network (IBSCRFSFNN), which combines the advantages of recurrent neural network, fuzzy logic system and feature selection method, is developed to approximate an idea BSC and to maintain the stability of SRM position drive system. The network structure and online learning algorithm of the IBSCRFSFNN are described in detail. At last, the proposed control system is implemented in a floating-point TMS320F28075 digital signal processor. The experimental results are illustrated to show the validity of the proposed intelligent BSC system.

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Intelligent Backstepping Control of Synchronous Reluctance Motor Drive System

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Intelligent Control of Six-Phase Permanent Magnet Synchronous Motor Drive System for Electric Power Steering System(3/3)

Cite this