Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems

Chang Hung Hsu; Chia Wen Chang; Mu Jhe Jian; Chin Wang Tao

doi:10.1109/SMC.2018.00704

Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems

Chang Hung Hsu, Chia Wen Chang, Mu Jhe Jian, Chin Wang Tao

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

Abstract

The adaptive command-filtered backstepping controller (ACFBC) is proposed to deal with the consensus problem of two chaotic dynamic systems. The proposed ACFBC system is designed based on the finite-time stability theorem in combination with backstepping technique and command filtered compensation. Moreover, a neural network (NN) approximation technique is utilized to approximate the unknown nonlinear function in this paper. Stability of the closed-loop system is analyzed via Lyapunov direct method. Finally, simulation results have shown the validity the proposed ACFBC system for the chaotic systems regarding unknown dynamic function.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4155-4159
Number of pages	5
ISBN (Electronic)	9781538666500
DOIs	https://doi.org/10.1109/SMC.2018.00704
State	Published - 02 07 2018
Externally published	Yes
Event	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 - Miyazaki, Japan Duration: 07 10 2018 → 10 10 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Conference

Conference	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Country/Territory	Japan
City	Miyazaki
Period	07/10/18 → 10/10/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

adaptive control
chaotic system
command filtered backstepping
neural networks

UN SDGs

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

Access to Document

10.1109/SMC.2018.00704

Cite this

Hsu, C. H., Chang, C. W., Jian, M. J., & Tao, C. W. (2018). Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (pp. 4155-4159). Article 8616701 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2018.00704

Hsu, Chang Hung ; Chang, Chia Wen ; Jian, Mu Jhe et al. / Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems. Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 4155-4159 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

@inproceedings{02215efcd96b420788eb58cf452bb2b0,

title = "Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems",

abstract = "The adaptive command-filtered backstepping controller (ACFBC) is proposed to deal with the consensus problem of two chaotic dynamic systems. The proposed ACFBC system is designed based on the finite-time stability theorem in combination with backstepping technique and command filtered compensation. Moreover, a neural network (NN) approximation technique is utilized to approximate the unknown nonlinear function in this paper. Stability of the closed-loop system is analyzed via Lyapunov direct method. Finally, simulation results have shown the validity the proposed ACFBC system for the chaotic systems regarding unknown dynamic function.",

keywords = "adaptive control, chaotic system, command filtered backstepping, neural networks",

author = "Hsu, {Chang Hung} and Chang, {Chia Wen} and Jian, {Mu Jhe} and Tao, {Chin Wang}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 ; Conference date: 07-10-2018 Through 10-10-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/SMC.2018.00704",

language = "英语",

series = "Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018",

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

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Hsu, CH, Chang, CW, Jian, MJ & Tao, CW 2018, Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems. in Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018., 8616701, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 4155-4159, 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Miyazaki, Japan, 07/10/18. https://doi.org/10.1109/SMC.2018.00704

Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems. / Hsu, Chang Hung; Chang, Chia Wen; Jian, Mu Jhe et al.
Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 4155-4159 8616701 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

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

TY - GEN

T1 - Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems

AU - Hsu, Chang Hung

AU - Chang, Chia Wen

AU - Jian, Mu Jhe

AU - Tao, Chin Wang

PY - 2018/7/2

Y1 - 2018/7/2

N2 - The adaptive command-filtered backstepping controller (ACFBC) is proposed to deal with the consensus problem of two chaotic dynamic systems. The proposed ACFBC system is designed based on the finite-time stability theorem in combination with backstepping technique and command filtered compensation. Moreover, a neural network (NN) approximation technique is utilized to approximate the unknown nonlinear function in this paper. Stability of the closed-loop system is analyzed via Lyapunov direct method. Finally, simulation results have shown the validity the proposed ACFBC system for the chaotic systems regarding unknown dynamic function.

AB - The adaptive command-filtered backstepping controller (ACFBC) is proposed to deal with the consensus problem of two chaotic dynamic systems. The proposed ACFBC system is designed based on the finite-time stability theorem in combination with backstepping technique and command filtered compensation. Moreover, a neural network (NN) approximation technique is utilized to approximate the unknown nonlinear function in this paper. Stability of the closed-loop system is analyzed via Lyapunov direct method. Finally, simulation results have shown the validity the proposed ACFBC system for the chaotic systems regarding unknown dynamic function.

KW - adaptive control

KW - chaotic system

KW - command filtered backstepping

KW - neural networks

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DO - 10.1109/SMC.2018.00704

M3 - 会议稿件

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SP - 4155

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BT - Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Y2 - 7 October 2018 through 10 October 2018

ER -

Hsu CH, Chang CW, Jian MJ, Tao CW. Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 4155-4159. 8616701. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). doi: 10.1109/SMC.2018.00704

Adaptive Command-Filtered Backstepping Control for Chaotic Dynamic Systems

Abstract

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Bibliographical note

Keywords

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