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

JCR Impact Factor: 19.2, Top 1 (SCI Q1)

CiteScore: 28.2, Top 1% (Q1)
Google Scholar h5-index: 95， TOP 5

Turn off MathJax

Article Contents

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

Citation:

PDF( 1450 KB)

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

More Information

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

FullText(HTML)

References(37)

References

[1]	T. K. Chang, A. Spowage, and K. Y. Chan, "Review of control and sensor system of flexible manipulator, " Journal of Intelligent & Robotic Systems, vol. 77, no. 1, pp. 187-213, 2015. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=fb5cfc55d19d36e3412e9634fd4625fd
[2]	K. Melhem and W. Wang, "Global output tracking control of flexible joint robots via factorization of the manipulator mass matrix, " IEEE Transactions on Robotics, vol. 25, no. 2, pp. 428-437, 2009. doi: 10.1109/TRO.2009.2012016
[3]	J. R. Forbes and C. J. Damaren, "Design of optimal strictly positive real controllers using numerical optimization for the control of flexible robotic systems, " Journal of the Franklin Institute, vol. 348, no. 8, pp. 2191-2215, 2011. doi: 10.1016/j.jfranklin.2011.06.013
[4]	J. Kim and E. A. Croft, "Full-state tracking control for flexible joint robots with singular perturbation techniques, " IEEE Transactions on Control Systems Technology, doi: 10.1109/TCST.2017.2756962.
[5]	A. C. Huang and Y. C. Chen, "Adaptive sliding control for single-link flexible-joint robot with mismatched uncertainties, " IEEE Transactions on Control Systems Technology, vol. 12, no. 5, pp. 770-775, 2004. doi: 10.1109/TCST.2004.826968
[6]	A. D. Luca, B. Siciliano, and L. Zollo, "Pd control with on-line gravity compensation for robots with elastic joints: Theory and experiments, " Automatica, vol. 41, no. 10, pp. 1809-1819, 2005. doi: 10.1016/j.automatica.2005.05.009
[7]	J. S. Bang, H. Shim, K. P. Sang, and H. S.Jin, "Robust tracking and vibration suppression for a two-inertia system by combining backstepping approach with disturbance observer, " IEEE Transactions on Industrial Electronics, vol. 57, no. 9, pp. 3197-3206, 2010. doi: 10.1109/TIE.2009.2038398
[8]	S. K. Min and S. L. Jin, "Adaptive tracking control of flexible-joint manipulators without overparametrization, " Journal of Robotic Systems, vol. 21, no. 7, pp. 369-379, 2004. doi: 10.1002/(ISSN)1097-4563
[9]	W. Chang, Y. Li, and S. Tong, "Adaptive fuzzy backstepping tracking control for flexible robotic manipulator, " IEEE/CAA J. Autom. Sinica, doi: 10.1109/JAS.2017.7510886, 2017.
[10]	D. Swaroop, J. K. Hedrick, P. P. Yip, and J. C. Gerdes, "Dynamic surface control for a class of nonlinear systems, " IEEE Transactions on Automatic Control, vol. 45, no. 10, pp. 1893-1899, 2002. http://d.old.wanfangdata.com.cn/Periodical/kzyjc201202019
[11]	W. Si and X. Dong, "Adaptive neural dsc for nonlinear switched systems with prescribed performance and input saturation, " IEEE/CAA J. Autom. Sinica, doi: 10.1109/JAS.2017.7510661, 2017.
[12]	S. Su, "Output-feedback dynamic surface control for a class of nonlinear non-minimum phase systems, " IEEE/CAA J. Autom. Sinica, vol. 3, no. 1, pp. 96-104, 2016. doi: 10.1109/JAS.2016.7373767
[13]	H. Wang, P. X. Liu, and B. Niu, "Robust fuzzy adaptive tracking control for nonaffine stochastic nonlinear switching systems, " IEEE Transactions on Cybernetics, vol. 48, no. 8, pp. 2462-2471, 2018. doi: 10.1109/TCYB.2017.2740841
[14]	M. M. Polycarpou, "Stable adaptive neural control scheme for nonlinear systems, " IEEE Transactions on Automatic Control, vol. 41, no. 3, pp. 447-451, 2002. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=79932ab111d6e2a3dbe6f3874f279c87
[15]	L. X. Wang and J. M. Mendel, "Fuzzy basis functions, universal approximation, and orthogonal least-squares learning, " IEEE Transactions on Neural Networks, vol. 3, no. 5, pp. 807-814, 1992. doi: 10.1109/72.159070
[16]	L. Jin, S. Li, H. M. La, and X. Luo, "Manipulability optimization of redundant manipulators using dynamic neural networks, " IEEE Transactions on Industrial Electronics, vol. 64, no. 6, pp. 4710-4720, 2017. doi: 10.1109/TIE.2017.2674624
[17]	Y. Zhang, S. Li, J. Gui, and X. Luo, "Velocity-level control with compliance to acceleration-level constraints: A novel scheme for manipulator redundancy resolution, " IEEE Transactions on Industrial Informatics, vol. 14, no. 3, pp. 921-930, 2018. doi: 10.1109/TII.2017.2737363
[18]	S. C. Tong, X. L. He, and H. G. Zhang, "A combined backstepping and small-gain approach to robust adaptive fuzzy output feedback control, " IEEE Transactions on Fuzzy Systems, vol. 17, no. 5, pp. 1059-1069, 2009. doi: 10.1109/TFUZZ.2009.2021648
[19]	M. Mirshekaran, F. Piltan, Z. Esmaeili, T. Khajeaian, and M. Kazeminasab, "Design sliding mode modified fuzzy linear controller with application to flexible robot manipulator, " International Journal of Modern Education & Computer Science, vol. 5, no. 10, pp. 53-63, 2013. http://cn.bing.com/academic/profile?id=907ce5894f0ad5df8127d450044cb20b&encoded=0&v=paper_preview&mkt=zh-cn
[20]	H. Chaoui, W. Gueaieb, M. Biglarbegian, and M. C. E. Yagoub, "Computationally efficient adaptive type-2 fuzzy control of flexible-joint manipulators, " Robotics, vol. 2, no. 2, pp. 66-91, 2013. doi: 10.3390/robotics2020066
[21]	X. Luo, M. Zhou, S. Li, Y. Xia, Z. H. You, Q. Zhu, and H. Leung, "Incorporation of efficient second-order solvers into latent factor models for accurate prediction of missing QoS data, " IEEE Transactions on Cybernetics, vol. 48, no. 4, pp. 1216-1228, 2018. doi: 10.1109/TCYB.2017.2685521
[22]	S. Li, Z. H. You, H. Guo, X. Luo, and Z. Q. Zhao, "Inverse-free extreme learning machine with optimal information updating, " IEEE Transactions on Cybernetics, vol. 46, no. 5, pp. 1229-1241, 2016. doi: 10.1109/TCYB.2015.2434841
[23]	P. Sun and Z. Yu, "Tracking control for a cushion robot based on fuzzy path planning with safe angular velocity, " IEEE/CAA J. Autom. Sinica, vol. 4, no. 4, pp. 610-619, 2017. doi: 10.1109/JAS.2017.7510607
[24]	X. Luo, J. Sun, Z. Wang, S. Li, and M. Shang, "Symmetric and nonnegative latent factor models for undirected, high dimensional and sparse networks in industrial applications, " IEEE Transactions on Industrial Informatics, vol. 13, no. 6, pp. 3098-3107, 2017. doi: 10.1109/TII.2017.2724769
[25]	X. Luo, M. Zhou, S. Li, Z. You, Y. Xia, and Q. Zhu, "A nonnegative latent factor model for large-scale sparse matrices in recommender systems via alternating direction method, " IEEE Transactions on Neural Networks & Learning Systems, vol. 27, no. 3, pp. 579-592, 2016. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=1b3a26299d2a8a0d45fbd4e4d51f20d1
[26]	S. Li, M. C. Zhou, X. Luo, and Z. H. You, "Distributed winner-takeall in dynamic networks, " IEEE Transactions on Automatic Control, vol. 62, no. 2, pp. 577-589, 2017. doi: 10.1109/TAC.2016.2578645
[27]	H. Yang and J. Liu, "An adaptive rbf neural network control method for a class of nonlinear systems, " IEEE/CAA J. Autom. Sinica, vol. 5, no. 2, pp. 457-462, 2018. doi: 10.1109/JAS.2017.7510820
[28]	X. Luo, M. Zhou, Y. Xia, Q. Zhu, A. C. Ammari, and A. Alabdulwahab, "Generating highly accurate predictions for missing qos data via aggregating nonnegative latent factor models, " IEEE Transactions on Neural Networks & Learning Systems, vol. 27, no. 3, pp. 524-537, 2015. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=9ea020b4a53845c6ba1596b8192872c5
[29]	Y. Yang, J. Tan, and D. Yue, "Prescribed performance control of onedof link manipulator with uncertainties and input saturation constraint, " IEEE/CAA J. Autom. Sinica, doi: 10.1109/JAS.2018.7511099, 2018.
[30]	Y. Li, S. Tong, and T. Li, "Hybrid fuzzy adaptive output feedback control design for uncertain mimo nonlinear systems with time-varying delays and input saturation, " IEEE Transactions on Fuzzy Systems, vol. 24, no. 4, pp. 841-853, 2016. doi: 10.1109/TFUZZ.2015.2486811
[31]	Y. Li, S. Tong, and T. Li, "Composite adaptive fuzzy output feedback control design for uncertain nonlinear strict-feedback systems with input saturation, " IEEE Transactions on Cybernetics, vol. 45, no. 10, pp. 2299-2308, 2015. doi: 10.1109/TCYB.2014.2370645
[32]	Q. Zhou, H. Li, C. Wu, L. Wang, and C. K. Ahn, "Adaptive fuzzy control of nonlinear systems with unmodeled dynamics and input saturation using small-gain approach, " IEEE Transactions on Systems Man & Cybernetics Systems, vol. 47, no. 8, pp. 1979-1989, 2017. http://ieeexplore.ieee.org/document/7572123/
[33]	X. Zhao, H. Yang, W. Xia, and X. Wang, "Adaptive fuzzy hierarchical sliding-mode control for a class of mimo nonlinear time-delay systems with input saturation, " IEEE Transactions on Fuzzy Systems, vol. 25, no. 5, pp. 1062-1077, 2017. doi: 10.1109/TFUZZ.2016.2594273
[34]	R. Bai, "Adaptive sliding-mode control of automotive electronic throttle in the presence of input saturation constraint, " IEEE/CAA J. Autom. Sinica, vol. 5, no. 4, pp. 878-884, 2018. doi: 10.1109/JAS.2018.7511147
[35]	Z. Fu, W. Xie, S. Rakheja, and J. Na, "Observer-based adaptive optimal control for unknown singularly perturbed nonlinear systems with input constraints, " IEEE/CAA J. Autom. Sinica, vol. 4, no. 1, pp. 48-57, 2017. doi: 10.1109/JAS.2017.7510322
[36]	S. J. Yoo, J. B. Park, and Y. H. Choi, Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks, " IEEE Transactions on Systems Man & Cybernetics, Part B Cybernetics, vol. 36, no. 3, pp. 1342-1355, 2006. http://europepmc.org/abstract/MED/17186810
[37]	B. Ren, P. P. San, S. S. Ge, and H. L. Tong, "Adaptive dynamic surface control for a class of strict-feedback nonlinear systems with unknown backlash-like hysteresis, " in Proc. 2009 American Control Conference, St. Louis, MO, USA, 2009, pp. 4482-4487.

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(7) / Tables(3)

Get Citation

PDF

XML

Article Metrics

Article views (2261) PDF downloads(119)

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

doi: 10.1109/JAS.2019.1911330

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Export File

Citation

Format

Content