Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems

Kunpeng Zhang; Zhuang Liu; Ruiqi Xu; Dongling Yu; Deshan Kong; Qichao Guan; Yue Zhao

doi:10.1109/CAC57257.2022.10054657

Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems

Kunpeng Zhang
, Zhuang Liu
, Ruiqi Xu
, Dongling Yu
, Deshan Kong
, Qichao Guan
, Yue Zhao^*

^*Corresponding author for this work

School of Astronautics

Research Institute
Harbin Institute of Technology
Harbin Engineering University

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

2 Scopus citations

Abstract

In this paper, a controller which can achieve fixed-time convergence is studied for manipulator systems. Firstly, an adaptive neural network (ANN) is used to estimate the unknown parts and external disturbances of the system. Secondly, a piecewise sliding mode variable is used to realize the nonsingular control of the terminal sliding mode. Then, in order to improve the tracking speed of the manipulator system, a faster fixed-time control algorithm is designed, and the tracking error can converge within a faster fixed-time. Finally, the practicability of the proposed algorithm is verified by simulation.

Original language	English
Title of host publication	Proceedings - 2022 Chinese Automation Congress, CAC 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3324-3329
Number of pages	6
ISBN (Electronic)	9781665465335
DOIs	https://doi.org/10.1109/CAC57257.2022.10054657
State	Published - 2022
Event	2022 Chinese Automation Congress, CAC 2022 - Xiamen, China Duration: 25 Nov 2022 → 27 Nov 2022

Publication series

Name	Proceedings - 2022 Chinese Automation Congress, CAC 2022
Volume	2022-January

Conference

Conference	2022 Chinese Automation Congress, CAC 2022
Country/Territory	China
City	Xiamen
Period	25/11/22 → 27/11/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Neural network
fixed-time control
manipulator systems
sliding mode control

Access to Document

10.1109/CAC57257.2022.10054657

Cite this

Zhang, K., Liu, Z., Xu, R., Yu, D., Kong, D., Guan, Q., & Zhao, Y. (2022). Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems. In Proceedings - 2022 Chinese Automation Congress, CAC 2022 (pp. 3324-3329). (Proceedings - 2022 Chinese Automation Congress, CAC 2022; Vol. 2022-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAC57257.2022.10054657

@inproceedings{3c727f57bd4a45f994a14506a0613bd8,

title = "Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems",

abstract = "In this paper, a controller which can achieve fixed-time convergence is studied for manipulator systems. Firstly, an adaptive neural network (ANN) is used to estimate the unknown parts and external disturbances of the system. Secondly, a piecewise sliding mode variable is used to realize the nonsingular control of the terminal sliding mode. Then, in order to improve the tracking speed of the manipulator system, a faster fixed-time control algorithm is designed, and the tracking error can converge within a faster fixed-time. Finally, the practicability of the proposed algorithm is verified by simulation.",

keywords = "Neural network, fixed-time control, manipulator systems, sliding mode control",

author = "Kunpeng Zhang and Zhuang Liu and Ruiqi Xu and Dongling Yu and Deshan Kong and Qichao Guan and Yue Zhao",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Chinese Automation Congress, CAC 2022 ; Conference date: 25-11-2022 Through 27-11-2022",

year = "2022",

doi = "10.1109/CAC57257.2022.10054657",

language = "英语",

series = "Proceedings - 2022 Chinese Automation Congress, CAC 2022",

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

pages = "3324--3329",

booktitle = "Proceedings - 2022 Chinese Automation Congress, CAC 2022",

address = "美国",

}

Zhang, K, Liu, Z, Xu, R, Yu, D, Kong, D, Guan, Q & Zhao, Y 2022, Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems. in Proceedings - 2022 Chinese Automation Congress, CAC 2022. Proceedings - 2022 Chinese Automation Congress, CAC 2022, vol. 2022-January, Institute of Electrical and Electronics Engineers Inc., pp. 3324-3329, 2022 Chinese Automation Congress, CAC 2022, Xiamen, China, 25/11/22. https://doi.org/10.1109/CAC57257.2022.10054657

Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems. / Zhang, Kunpeng; Liu, Zhuang; Xu, Ruiqi et al.
Proceedings - 2022 Chinese Automation Congress, CAC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 3324-3329 (Proceedings - 2022 Chinese Automation Congress, CAC 2022; Vol. 2022-January).

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

TY - GEN

T1 - Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems

AU - Zhang, Kunpeng

AU - Liu, Zhuang

AU - Xu, Ruiqi

AU - Yu, Dongling

AU - Kong, Deshan

AU - Guan, Qichao

AU - Zhao, Yue

PY - 2022

Y1 - 2022

N2 - In this paper, a controller which can achieve fixed-time convergence is studied for manipulator systems. Firstly, an adaptive neural network (ANN) is used to estimate the unknown parts and external disturbances of the system. Secondly, a piecewise sliding mode variable is used to realize the nonsingular control of the terminal sliding mode. Then, in order to improve the tracking speed of the manipulator system, a faster fixed-time control algorithm is designed, and the tracking error can converge within a faster fixed-time. Finally, the practicability of the proposed algorithm is verified by simulation.

AB - In this paper, a controller which can achieve fixed-time convergence is studied for manipulator systems. Firstly, an adaptive neural network (ANN) is used to estimate the unknown parts and external disturbances of the system. Secondly, a piecewise sliding mode variable is used to realize the nonsingular control of the terminal sliding mode. Then, in order to improve the tracking speed of the manipulator system, a faster fixed-time control algorithm is designed, and the tracking error can converge within a faster fixed-time. Finally, the practicability of the proposed algorithm is verified by simulation.

KW - Neural network

KW - fixed-time control

KW - manipulator systems

KW - sliding mode control

UR - https://www.scopus.com/pages/publications/85151053220

U2 - 10.1109/CAC57257.2022.10054657

DO - 10.1109/CAC57257.2022.10054657

M3 - 会议稿件

AN - SCOPUS:85151053220

T3 - Proceedings - 2022 Chinese Automation Congress, CAC 2022

SP - 3324

EP - 3329

BT - Proceedings - 2022 Chinese Automation Congress, CAC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 Chinese Automation Congress, CAC 2022

Y2 - 25 November 2022 through 27 November 2022

ER -

Zhang K, Liu Z, Xu R, Yu D, Kong D, Guan Q et al. Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems. In Proceedings - 2022 Chinese Automation Congress, CAC 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 3324-3329. (Proceedings - 2022 Chinese Automation Congress, CAC 2022). doi: 10.1109/CAC57257.2022.10054657

Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems

Abstract

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Keywords

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