Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation

Song Ling; Huanqing Wang; Peter X. Liu

doi:10.1109/JAS.2019.1911330

Volume 6 Issue 1

Jan. 2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2019 > 6(1): 97-107

Song Ling, Huanqing Wang and Peter X. Liu, "Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 97-107, Jan. 2019. doi: 10.1109/JAS.2019.1911330

Citation:

Song Ling, Huanqing Wang and Peter X. Liu, "Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 97-107, Jan. 2019. doi: 10.1109/JAS.2019.1911330

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Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation

doi: 10.1109/JAS.2019.1911330

Song Ling^1
,,
Huanqing Wang^{2
,
,},
Peter X. Liu^{3
,
,}

1.
School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China
2.
Department of Mathematics, Bohai University, Jinzhou 121000, China
3.
Department of Systems and Computer Engineering, Carleton University, Ottawa, ON KIS5B6, Canada

Funds:

the National Natural Science Foundation of China 61773051

the National Natural Science Foundation of China 61773072

the National Natural Science Foundation of China 61761166011

the Fundamental Research Fund for the Central Universities 2016RC021

the Fundamental Research Fund for the Central Universities 2017JBZ003

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Author Bio:
Song Ling graduated from North University of China, China, in 2016.He is currently pursuing the Ph.D.degree with the School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, China.His research interests include neural networks, fuzzy systems, backstepping control, nonlinear system control, and robot control. (e-mail: songling@bjtu.edu.cn)

Huanqing Wang received the B.Sc.degree in mathematics from Bohai University, Jinzhou, China, in 2003, the M.Sc.degree in mathematics from Inner Mongolia University, Huhhot, China, in 2006, and the Ph.D.degree from the Institute of Complexity Science, Qingdao University, Qingdao, China, in 2013.
He was a Post-Doctoral Fellow with the Department of Electrical Engineering, Lakehead University, Canada, in 2014, and was a Post-Doctoral Fellow with the Department of Systems and Computer Engineering, Carleton University, Canada.He has authored or co-authored over 40 papers in top international journals.His current research interests include adaptive backstepping control, fuzzy control, neural networks control, stochastic nonlinear systems.
Dr.Wang serves as an Associate Editor for several journals, including Neural Computing and Applications, International Journal of Control, Automation, and Systems, and IEEE Access. (e-mail: ndwhq@163.com)

Peter X. Liu (SM'07-F'19) received the B.Sc.and M.Sc.degrees from Northern Jiaotong University, China in 1992 and 1995, respectively, and Ph.D.degree from the University of Alberta, Canada in 2002.
He has been with the Department of Systems and Computer Engineering, Carleton University, Canada since July 2002 and he is currently a Professor.He is also with the school of Mechanical, Electronic andControt Engineering, Beijing Jiaotong University as an Adjunct Professor.Dr.Liu has published more than 300 research articles.His research interest includes interactive networked systems and teleoperation, haptics, surgical simulation, robotics, intelligent systems, and context-aware systems.
Dr.Liu serves as an Associate Editor for several journals including IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Cybernetics, IEEE Transactions on Automation Science and Engineering, and IEEE Access.He is a licensed member of the Professional Engineers of Ontario (P.Eng), a Fellow of IEEE and a Fellow of Engineering Institute of Canada (FEIC). (e-mail: xpliu@sce.carleton.ca)
Corresponding author: Huanqing Wang, e-mail: ndwhq@163.com; Peter X. Liu, e-mail: xpliu@sce.carleton.ca
Received Date: 2018-07-12
Revised Date: 2018-09-02
Accepted Date: 2018-09-10

Abstract

Abstract

In this paper, we propose an adaptive fuzzy dynamic surface control (DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal with the difficulties associated with input saturation. An adaptive DSC design with an auxiliary first-order filter is used to solve the "explosion of complexity" problem. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The main advantage of the proposed method is that only one adaptation parameter needs to be updated, which reduces the computational burden significantly. Simulation results demonstrate the feasibility of the proposed scheme and the comparison results show that the improved DSC method can reduce the computational burden by almost two thirds in comparison with the standard DSC method.
- Adaptive fuzzy control,
- dynamic surface control (DSC),
- flexible-joint (FJ) robots,
- single-link,
- tracking control

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References(37)

References

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Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation

doi: 10.1109/JAS.2019.1911330

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