Robust Consensus Tracking Control of Uncertain Multi-Agent Systems With Local Disturbance Rejection

Pan Yu; Kang-Zhi Liu; Xudong Liu; Xiaoli Li; Min Wu; Jinhua She

doi:10.1109/JAS.2023.123231

Volume 10 Issue 2

Feb. 2023

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2023 > 10(2): 427-438

P. Yu, K.-Z. Liu, X. D. Liu, X. L. Li, M. Wu, and J. She, “Robust consensus tracking control of uncertain multi-agent systems with local disturbance rejection,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 427–438, Feb. 2023. doi: 10.1109/JAS.2023.123231

Citation:

P. Yu, K.-Z. Liu, X. D. Liu, X. L. Li, M. Wu, and J. She, “Robust consensus tracking control of uncertain multi-agent systems with local disturbance rejection,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 427–438, Feb. 2023. doi: 10.1109/JAS.2023.123231

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Robust Consensus Tracking Control of Uncertain Multi-Agent Systems With Local Disturbance Rejection

doi: 10.1109/JAS.2023.123231

Pan Yu^{1
,
,},
Kang-Zhi Liu^2
,,
Xudong Liu^1
,,
Xiaoli Li^3
,,
Min Wu^4
,,
Jinhua She^5
,

1.
Faculty of Information Technology and the Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing 100124, China
2.
Department of Electrical and Electronic Engineering, Chiba University, Chiba 263-8522, Japan
3.
Beijing Aerospace Automatic Control Institute, Beijing 100854, China
4.
School of Automation, China University of Geosciences, Wuhan 430074, China
5.
School of Engineering, Tokyo University of Technology, Hachioji, Tokyo 192-0982, Japan

Funds: This work was supported by the National Natural Science Foundation of China (62003010, 61873006, 61673053), the Beijing Postdoctoral Research Foundation (Q6041001202001), the Postdoctoral Research Foundation of Chaoyang District (Q1041001202101), and the National Key Research and Development Project (2018YFC1602704, 2018YFB1702704)

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Author Bio:
Pan Yu (Member, IEEE) received the B.S. and Ph.D. degrees in engineering from Central South University, in 2014 and 2019, respectively. She was a Research Student with the Department of Electrical and Electronic Engineering, Chiba University, Japan, from 2017 to 2019. In 2019, she joined Beijing University of Technology where she is currently an Associate Professor with the Faculty of Information Technology. Her research interests include multi-agent systems, repetitive control, disturbance estimation and rejection, time-delay system, and robust control. Dr. Yu is a Member of the Chinese Association of Automation (CAA)

Kangzhi Liu (Senior Member, IEEE) received the B.E. degree in aeronautical engineering from Northwestern Polytechnical University, in 1984, and the M.E. and Ph.D. degrees in electrical engineering from Chiba University, Japan, in 1991 and 1998, respectively. Since then, he has been with Chiba University, where he is currently a Professor of control engineering and power system. He has authored and coauthored six books. His research interests include control theory, power systems, smart grids, and electrical drives. Dr. Liu is a Member of the Chinese Association of Automation (CAA). Dr. Liu was the recipient of the Young Author Award and three Best Paper Awards from the Society of Instrument and Control Engineers (SICE), Japan. He served as a Director of the SICE in 2017 and 2018

Xudong Liu received the B.S. degree from Central South University, in 2014, and the M.S. from Beihang University, in 2017, all in engineering. In 2017, he joined Beijing Aerospace Automatic Control Institute where he is currently an Engineer. His research interests include multi-agent systems, flight control, satellite navigation, and guidance and control

Xiaoli Li (Member, IEEE) received the B.S. degree from Dalian University of Technology, in 1997, and the Ph.D. degree from Northeastern University, in 2000, all in engineering. From 2000 to 2002, he was a Postdoctoral Research Fellow in the Department of Automation, Tsinghua University. In 2003, he was a Research Fellow in the Department of Control Engineering and System Analysis, University Libre de Bruxelles, Belgium. From 2004 to 2015, he was a Professor of the School of Automation and Electrical Engineering, University of Science and Technology Beijing. In 2016, he joined Beijing University of Technology where he is currently a Professor with the Faculty of Information Technology. His research interests cover artificial intelligence, multiple model control, and intelligent control. Dr. Li is a Member of the Chinese Association of Automation (CAA)

Min Wu (Fellow, IEEE) received the B.S. and M.S. degrees from Central South University in 1983 and 1986, respectively, and the Ph.D. degree from Tokyo Institute of Technology, Japan, in 1999, all in engineering. He was a Faculty Member of the School of Information Science and Engineering, Central South University, from 1986 to 2014, and became a Professor in 1994. In 2014, he joined the China University of Geosciences, where he is currently a Professor of control science and engineering in the School of Automation. He was a Visiting Scholar with the Department of Electrical Engineering, Tohoku University, Japan, from 1989 to 1990, and a Visiting Research Scholar with the Department of Control and Systems Engineering, Tokyo Institute of Technology, from 1996 to 1999. He was a Visiting Professor with the School of Mechanical, Materials, Manufacturing Engineering and Management, University of Nottingham, U.K., from 2001 to 2002. His current research interests include robust control, process control, and intelligent systems. Dr. Wu is a Fellow of the Chinese Association of Automation (CAA). He received the International Federation of Automatic Control (IFAC) Control Engineering Practice Prize Paper Award in 1999 (together with M. Nakano and J. She)

Jinhua She (Fellow, IEEE) received the B.S. degree from Central South University in 1983, and the M.S. and Ph.D. degrees from the Tokyo Institute of Technology, Japan, in 1990 and 1993, respectively, all in engineering. In 1993, he joined the School of Engineering, Tokyo University of Technology, where he is currently a Professor. His research interests include the application of control theory, repetitive control, process control, m-learning, and assistive robotics. Dr. She is a Member of the Chinese Association of Automation (CAA), the Society of Instrument and Control Engineers (SICE), Institute of Electrical Engineers of Japan (IEEJ), the Japan Society of Mechanical Engineers (JSME), Architectural Institute of Japan (AIJ), and the Asian Control Association (ACA). He was the Recipient of the International Federation of Automatic Control (IFAC) Control Engineering Practice Paper Prize in 1999 (jointly with M. Wu and M. Nakano)
Corresponding author: Pan Yu, e-mail: panyu@bjut.edu.cn
Received Date: 2022-05-13
Accepted Date: 2022-06-12

Available Online: 2022-12-02

Abstract

Abstract

In this paper, a new distributed consensus tracking protocol incorporating local disturbance rejection is devised for a multi-agent system with heterogeneous dynamic uncertainties and disturbances over a directed graph. It is of two-degree-of-freedom nature. Specifically, a robust distributed controller is designed for consensus tracking, while a local disturbance estimator is designed for each agent without requiring the input channel information of disturbances. The condition for asymptotic disturbance rejection is derived. Moreover, even when the disturbance model is not exactly known, the developed method also provides good disturbance-rejection performance. Then, a robust stabilization condition with less conservativeness is derived for the whole multi-agent system. Further, a design algorithm is given. Finally, comparisons with the conventional one-degree-of-freedom-based distributed disturbance-rejection method for mismatched disturbances and the distributed extended-state observer for matched disturbances validate the developed method.
- Directed graph,
- distributed control,
- disturbance rejection,
- dynamic uncertainties,
- multi-agent systems,
- robust control

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References

[1]	R. W. Beard, T. W. McLain, M. A. Goodrich, and E. Anderson, “Coordinated target assignment and intercept for unmanned air vehicles,” IEEE Trans. Robot. Autom., vol. 18, no. 6, pp. 911–922, Dec. 2002. doi: 10.1109/TRA.2002.805653
[2]	J. R. Carpenter, “Decentralized control of satellite formations,” Int. J. Robust Nonlinear Control, vol. 12, no. 2/3, pp. 141–161, Feb./Mar. 2002.
[3]	Z. Li, Z. Duan, G. Chen, and L. Huang, “Consensus of multiagent systems and synchronization of complex networks: A unified viewpoint,” IEEE Trans. Circuits Syst. I, vol. 57, no. 1, pp. 213–224, 2010. doi: 10.1109/TCSI.2009.2023937
[4]	X. Li, Y. C. Soh, and L. Xie, “Output-feedback protocols without controller interaction for consensus of homogeneous multi-agent systems: A unified robust control view,” Automatica, vol. 81, pp. 37–45, 2017. doi: 10.1016/j.automatica.2017.03.001
[5]	Q. Wei, X. Wang, X. Zhong, and N. Wu, “Consensus control of leader-following multi-agent systems in directed topology with heterogeneous disturbances,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 2, pp. 423–431, Feb. 2021. doi: 10.1109/JAS.2021.1003838
[6]	A. Elahi, A. Alfi, and H. Modares, “H_∞ consensus control of discrete-time multi-agent systems under network imperfections and external disturbance,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 667–675, May 2019. doi: 10.1109/JAS.2019.1911474
[7]	Y. Z. Lv, Z. K. Li, and Z. S. Duan, “Distributed PI control for consensus of heterogeneous multiagent systems over directed graphs,” IEEE Trans. Syst. Man Cybern. Syst., vol. 50, no. 4, pp. 1602–1609, Apr. 2020. doi: 10.1109/TSMC.2018.2792472
[8]	Q. Wang, Z. Duan, and J. Wang, “Distributed optimal consensus control algorithm for continuous-time multi-agent systems,” IEEE Trans. Circuits Syst. Ⅱ-Express Briefs, vol. 67, no. 1, pp. 102–106, Jan. 2020. doi: 10.1109/TCSII.2019.2900758
[9]	H. Zhang, J. Han, Y. Wang, and H. Jiang, “H_∞ consensus for linear heterogeneous discrete-time multiagent systems with output feedback control,” IEEE Trans. Cybern., vol. 49, no. 10, pp. 3713–3721, Oct. 2019. doi: 10.1109/TCYB.2018.2849361
[10]	K.-Z. Liu and Y. Yao, Robust Control: Theory and Applications. Hoboken, NJ, USA: Wiley, 2016.
[11]	M. Guo, D. Xu, and L. Liu, “Design of cooperative output regulators for heterogeneous uncertain nonlinear multiagent systems,” IEEE Trans. Cybern., vol. 52, no. 6, pp. 5174–5183, 2022.
[12]	Y. Hua, X. Dong, Q. Li, and Z. Ren, “Distributed time-varying formation robust tracking for general linear multiagent systems with parameter uncertainties and external disturbances,” IEEE Trans. Cybern., vol. 47, no. 8, pp. 1959–1969, Aug. 2017. doi: 10.1109/TCYB.2017.2701889
[13]	J. Huang, Nonlinear Output Regulation: Theory and Applications. Philadelphia, PA, USA: SIAM, 2004.
[14]	X. Wang, Y. Hong, J. Huang, and Z.-P. Jiang, “A distributed control approach to a robust output regulation problem for multi-agent linear systems,” IEEE Trans. Automat. Control, vol. 55, no. 12, pp. 2891–2895, Dec. 2010. doi: 10.1109/TAC.2010.2076250
[15]	Y. Su, Y. Hong, and J. Huang, “A general result on the robust cooperative output regulation for linear uncertain multi-agent systems,” IEEE Trans. Automat. Control, vol. 58, no. 5, pp. 1275–1279, May 2013. doi: 10.1109/TAC.2012.2229837
[16]	H. L. Trentelman, K. Takaba, and N. Monshizadeh, “Robust synchronization of uncertain linear multi-agent systems,” IEEE Trans. Autom. Control, vol. 58, no. 6, pp. 1511–1523, Jun. 2013. doi: 10.1109/TAC.2013.2239011
[17]	X. Li, Y. C. Soh, and L. Xie, “Design of output-feedback protocols for robust consensus of uncertain linear multi-agent systems,”in Proc. Amer. Control Conf., Seattle, WA, USA, 2017, pp. 936–941.
[18]	W. H. Chen, J. Yang, L. Guo, and S. Li, “Disturbance observer-based control and related methods: An overview,” IEEE Trans. Ind. Electron., vol. 63, no. 2, pp. 1083–1095, Feb. 2016. doi: 10.1109/TIE.2015.2478397
[19]	K. Liu, Y. Chen, Z. Duan, and J. Lu, “Cooperative output regulation of LTI plant via distributed observers with local measurement,” IEEE Trans. Cybern., vol. 48, no. 7, pp. 2181–2191, Jul. 2018. doi: 10.1109/TCYB.2017.2728812
[20]	X. Li, Y. C. Soh, L. Xie, and F. L. Lewis, “Cooperative output regulation of heterogeneous linear multi-agent networks via H_∞ performance allocation,” IEEE Trans. Automat. Control, vol. 64, no. 2, pp. 683–696, Feb. 2019.
[21]	Y. Huo, Y. Lv, X. Wu, and Z. Duan, “Fully distributed consensus for general linear multi-agent systems with unknown external disturbances,” IET Contr. Theory Appl., vol. 13, no. 16, pp. 2595–2609, Oct. 2019. doi: 10.1049/iet-cta.2018.6457
[22]	G. Li, X. Wang, S. Li, W. X. Zheng, and X. Chen, “Finite-time output consensus of second-order multi-agent systems with mismatched disturbances via active anti-disturbance control,”in Proc. 11th Asian Control Conf., Gold Coast, QLD, 2017, pp. 2042–2047.
[23]	Q. Wang and C. Sun, “Distributed asymptotic consensus in directed networks of nonaffine systems with nonvanishing disturbance,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 6, pp. 1133–1140, Jun. 2021. doi: 10.1109/JAS.2021.1004021
[24]	J. She, M. Fang, Q. Ohyama, H. Hashimoto, and M. Wu, “Improving disturbance-rejection performance based on an equivalent-input-disturbance approach,” IEEE Trans. Ind. Electron., vol. 55, no. 1, pp. 380–389, Jan. 2008. doi: 10.1109/TIE.2007.905976
[25]	Y u, K. Liu, X. Liu, X. Li, J. She, and M. Wu, “Analysis of equivalent-input-disturbance-based control systems and a coordinated design algorithm for uncertain systems,” Int. J. Robust Nonlinear Control, vol. 31, no. 5, pp. 1755–1773, Jan. 2021. doi: 10.1002/rnc.5375
[26]	K. M. Zhou, J. C. Doyle, and K. Glover, Robust and Optimal Control. Englewood Cliffs, NJ, USA: Prentice-Hall, 1996.
[27]	Z. Ding, “Consensus disturbance rejection with disturbance observers,” IEEE Trans. Ind. Electron., vol. 62, no. 9, pp. 5829–5837, Sep. 2015. doi: 10.1109/TIE.2015.2442218
[28]	X. Wang, G. Wang, and S. Li, “Distributed finite-time optimization for integrator chain multiagent systems with disturbances,” IEEE Trans. Autom. Control, vol. 65, no. 12, pp. 5296–5311, Dec. 2020. doi: 10.1109/TAC.2020.2979274
[29]	X. Wang, S. Li, and G. Wang, “Distributed optimization for disturbed second-order multiagent systems based on active anti-disturbance control,” IEEE Trans. Neural Netw. Learn. Syst., vol. 31, no. 6, pp. 2104–2117, Jun. 2020. doi: 10.1109/TNNLS.2019.2951790
[30]	B. A. Francis, “The linear multivariable regulator problem,” SIAM J. Control Optimiz., vol. 15, no. 3, pp. 486–505, 1977. doi: 10.1137/0315033
[31]	Q. Shen, B. Jiang, P. Shi, and J. Zhao, “Cooperative adaptive fuzzy tracking control for networked unknown nonlinear multiagent systems with time-varying actuator faults,” IEEE Trans. Fuzzy Syst., vol. 22, no. 3, pp. 494–504, Jun. 2014. doi: 10.1109/TFUZZ.2013.2260757
[32]	F. Yaghmaie, F. Lewis, and R. Su, “Output regulation of linear heterogeneous multi-agent systems via output and state feedback,” Automatica, vol. 67, pp. 157–164, 2016. doi: 10.1016/j.automatica.2016.01.040
[33]	S. Skogestad and I. Postlethwaite, Multivariable Feedback Control. Hoboken, NJ, USA: Wiley, 2001.
[34]	J. Gu, et al., “Design and flight testing evaluation of formation control laws,” IEEE Trans. Control Syst. Technol., vol. 14, no. 6, pp. 1105–1112, Nov. 2006. doi: 10.1109/TCST.2006.880203
[35]	Y. Liu, D. Yao, H. Li, and R. Lu, “Distributed cooperative compound tracking control for a platoon of vehicles with adaptive NN,” IEEE Trans. Cybern., vol. 52, no. 7, pp. 7039–7048, 2022.
[36]	Y. Liu, H. Li, Z. Zuo, X. Li, and R. Lu, “An overview of finite/fixed-time control and its application in engineering systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2106–2120, 2022.

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By only using the output information of the agents and its neighbors, a new consensus tracking protocol with 2-DOF of active disturbance-rejection control is devised
The condition for local disturbance rejection is derived, which clarifies the superiority over global disturbance rejection. That is, each agent needs only to deal with the disturbances subject to itself, without worrying about the ones interfering with the neighbors
Regardless of the disturbance input channels, asymptotic performance is theoretically guaranteed when an internal model of disturbances is incorporated. Further, the developed method also provides a good performance for unknown disturbances
A robust synchronization condition with less conservativeness is developed for a general multi-agent system with heterogeneous dynamic uncertainties over a directed graph, which is easy to check

Robust Consensus Tracking Control of Uncertain Multi-Agent Systems With Local Disturbance Rejection

doi: 10.1109/JAS.2023.123231

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