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

School of Automation

Beijing Institute of Technology

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

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020
Editors	Mingxuan Sun, Huaguang Zhang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1209-1213
Number of pages	5
ISBN (Electronic)	9781728159225
DOIs	https://doi.org/10.1109/DDCLS49620.2020.9275157
Publication status	Published - 20 Nov 2020
Event	9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020 - Liuzhou, China Duration: 20 Nov 2020 → 22 Nov 2020

Publication series

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

Conference

Conference	9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020
Country/Territory	China
City	Liuzhou
Period	20/11/20 → 22/11/20

Keywords

Disturbance observer
Extended state observer
Multi-motor driving servo system
Optimal sliding surface

Access to Document

10.1109/DDCLS49620.2020.9275157

Cite this

Hu, S., & Ren, X. (2020). Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. In M. Sun, & H. Zhang (Eds.), Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020 (pp. 1209-1213). Article 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. editor / Mingxuan Sun ; Huaguang Zhang. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 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",

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Hu, S & Ren, X 2020, Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. in M Sun & H Zhang (eds), 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., pp. 1209-1213, 9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020, Liuzhou, China, 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. ed. / Mingxuan Sun; Huaguang Zhang. Institute of Electrical and Electronics Engineers Inc., 2020. p. 1209-1213 9275157 (Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020).

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

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AU - Ren, Xuemei

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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

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M3 - Conference contribution

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

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Hu S, Ren X. Observer-based Optimal Adaptive Control for Multi-motor Driving Servo System. In Sun M, Zhang H, editors, Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference, DDCLS 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 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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Keywords

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