Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System

Shuangyi Hu; Xuemei Ren

doi:10.1109/DDCLS49620.2020.9275157

Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System

Shuangyi Hu, Xuemei Ren

自动化学院

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

2 引用（Scopus）

摘要

In this paper, an improved optimal sliding mode control strategy is proposed for multi-motor driving servo system. Some states of multi-motor drive system are not measurable and there exists unknown nonlinearity. To solve this problem, the disturbance observer and extended state observer are both applied to estimate the unknown states and nonlinearity. Based on optimal control theory, the optimal sliding surface is selected to guarantee the optimal dynamic performance of the sliding mode of the system. The effectiveness of designed control methods is illustrated by simulation results.

源语言	英语
主期刊名	Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020
编辑	Mingxuan Sun, Huaguang Zhang
出版商	Institute of Electrical and Electronics Engineers Inc.
页	1209-1213
页数	5
ISBN（电子版）	9781728159225
DOI	https://doi.org/10.1109/DDCLS49620.2020.9275157
出版状态	已出版 - 20 11月 2020
活动	9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020 - Liuzhou, 中国期限: 20 11月 2020 → 22 11月 2020

出版系列

姓名	Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020

会议

会议	9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020
国家/地区	中国
市	Liuzhou
时期	20/11/20 → 22/11/20

访问文件

10.1109/DDCLS49620.2020.9275157

其它文件与链接

链接到 Scopus 的出版物

引用此

Hu, S., & Ren, X. (2020). Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. 在 M. Sun, & H. Zhang (编辑), Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020 (页码 1209-1213). 文章 9275157 (Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DDCLS49620.2020.9275157

Hu, Shuangyi ; Ren, Xuemei. / Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020. 编辑 / Mingxuan Sun ; Huaguang Zhang. Institute of Electrical and Electronics Engineers Inc., 2020. 页码 1209-1213 (Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020).

@inproceedings{94594a5a42244fb4900df5766d64c83b,

title = "Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System",

abstract = "In this paper, an improved optimal sliding mode control strategy is proposed for multi-motor driving servo system. Some states of multi-motor drive system are not measurable and there exists unknown nonlinearity. To solve this problem, the disturbance observer and extended state observer are both applied to estimate the unknown states and nonlinearity. Based on optimal control theory, the optimal sliding surface is selected to guarantee the optimal dynamic performance of the sliding mode of the system. The effectiveness of designed control methods is illustrated by simulation results.",

keywords = "Disturbance observer, Extended state observer, Multi-motor driving servo system, Optimal sliding surface",

author = "Shuangyi Hu and Xuemei Ren",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020 ; Conference date: 20-11-2020 Through 22-11-2020",

year = "2020",

month = nov,

day = "20",

doi = "10.1109/DDCLS49620.2020.9275157",

language = "English",

series = "Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020",

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

pages = "1209--1213",

editor = "Mingxuan Sun and Huaguang Zhang",

booktitle = "Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020",

address = "United States",

}

Hu, S & Ren, X 2020, Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. 在 M Sun & H Zhang (编辑), Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020., 9275157, Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020, Institute of Electrical and Electronics Engineers Inc., 页码 1209-1213, 9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020, Liuzhou, 中国, 20/11/20. https://doi.org/10.1109/DDCLS49620.2020.9275157

Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. / Hu, Shuangyi; Ren, Xuemei.
Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020. 编辑 / Mingxuan Sun; Huaguang Zhang. Institute of Electrical and Electronics Engineers Inc., 2020. 页码 1209-1213 9275157 (Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System

AU - Hu, Shuangyi

AU - Ren, Xuemei

PY - 2020/11/20

Y1 - 2020/11/20

N2 - In this paper, an improved optimal sliding mode control strategy is proposed for multi-motor driving servo system. Some states of multi-motor drive system are not measurable and there exists unknown nonlinearity. To solve this problem, the disturbance observer and extended state observer are both applied to estimate the unknown states and nonlinearity. Based on optimal control theory, the optimal sliding surface is selected to guarantee the optimal dynamic performance of the sliding mode of the system. The effectiveness of designed control methods is illustrated by simulation results.

AB - In this paper, an improved optimal sliding mode control strategy is proposed for multi-motor driving servo system. Some states of multi-motor drive system are not measurable and there exists unknown nonlinearity. To solve this problem, the disturbance observer and extended state observer are both applied to estimate the unknown states and nonlinearity. Based on optimal control theory, the optimal sliding surface is selected to guarantee the optimal dynamic performance of the sliding mode of the system. The effectiveness of designed control methods is illustrated by simulation results.

KW - Disturbance observer

KW - Extended state observer

KW - Multi-motor driving servo system

KW - Optimal sliding surface

UR - http://www.scopus.com/inward/record.url?scp=85098912464&partnerID=8YFLogxK

U2 - 10.1109/DDCLS49620.2020.9275157

DO - 10.1109/DDCLS49620.2020.9275157

M3 - Conference contribution

AN - SCOPUS:85098912464

T3 - Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020

SP - 1209

EP - 1213

BT - Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020

A2 - Sun, Mingxuan

A2 - Zhang, Huaguang

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020

Y2 - 20 November 2020 through 22 November 2020

ER -

Hu S, Ren X. Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. 在 Sun M, Zhang H, 编辑, Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 页码 1209-1213. 9275157. (Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020). doi: 10.1109/DDCLS49620.2020.9275157

Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System

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