Cooperative Target Tracking of Multiple Autonomous Surface Vehicles Under Switching Interaction Topologies

Lang Ma; Yu-Long Wang; Qing-Long Han

doi:10.1109/JAS.2022.105509

Volume 10 Issue 3

Mar. 2023

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 15.3, Top 1 (SCI Q1)

CiteScore: 23.5, Top 2% (Q1)
Google Scholar h5-index: 77， TOP 5

Turn off MathJax

Article Contents

Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2023 > 10(3): 673-684

L. Ma, Y.-L. Wang, and Q.-L. Han, “Cooperative target tracking of multiple autonomous surface vehicles under switching interaction topologies,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 673–684, Mar. 2023. doi: 10.1109/JAS.2022.105509

Citation:

L. Ma, Y.-L. Wang, and Q.-L. Han, “Cooperative target tracking of multiple autonomous surface vehicles under switching interaction topologies,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 673–684, Mar. 2023. doi: 10.1109/JAS.2022.105509

Citation:

PDF( 1879 KB)

Cooperative Target Tracking of Multiple Autonomous Surface Vehicles Under Switching Interaction Topologies

doi: 10.1109/JAS.2022.105509

Lang Ma^1
,,
Yu-Long Wang^1
,,
Qing-Long Han^{2
,
,}

1.
Shanghai Key Laboratory of Power Station Automation Technology, and the School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
2.
School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne VIC 3122, Australia

Funds: This work was supported in part by the National Science Foundation of China (61873335, 61833011); and the Project of Science and Technology Commission of Shanghai Municipality, China (20ZR1420200, 21SQBS01600, 19510750300, 21190780300)

More Information

Author Bio:
Lang Ma received the B.S. degree in mathematics and the M.S. degree in operational research and cybernetics from Shandong University in 2014 and 2017, respectively. He is currently a Ph.D. candidate in control science and engineering at Shanghai University. His current research interests include networked control systems, multi-agent systems, and motion control for unmanned marine vehicles

Yu-Long Wang (Member, IEEE) received the B.S. degree in computer science and technology from Liaocheng University in 2000, and the M.S. and Ph.D. degrees in control science and engineering from Northwestern University, in 2006 and 2008, respectively. He was a Post-Doctoral Research Fellow and a Research Fellow with Central Queensland University, North Rockhampton, Australia, an Academic Visitor with the University of Adelaide, Australia, and a Professor with Jiangsu University of Science and Technology. In 2017, he was appointed as an Eastern Scholar by the Municipal Commission of Education, China, and joined Shanghai University, where he is currently a Professor. His current research interests include networked control systems, fault detection, and motion control for marine vehicles

Qing-Long Han (Fellow, IEEE) received the B.Sc. degree in mathematics from Shandong Normal University in 1983, and the M.Sc. and Ph.D. degrees in control engineering from East China University of Science and Technology, in 1992 and 1997, respectively. He is Pro Vice-Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology, Australia. He held various academic and management positions at Griffith University and Central Queensland University, Australia. His research interests include networked control systems, multi-agent systems, time-delay systems, smart grids, unmanned surface vehicles, and neural networks.Professor Han was awarded The 2021 Norbert Wiener Award (the Highest Award in systems science and engineering, and cybernetics) and The 2021 M. A. Sargent Medal (the Highest Award of the Electrical College Board of Engineers Australia). He was the recipient of The 2022 IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award, The 2021 IEEE/CAA Journal of Automatica Sinica Norbert Wiener Review Award, The 2020 IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award, The 2020 IEEE Transactions on Industrial Informatics Outstanding Paper Award, and The 2019 IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award.Professor Han is a Member of the Academia Europaea (The Academy of Europe). He is a Fellow of The International Federation of Automatic Control (IFAC) and a Fellow of The Institution of Engineers Australia (IEAust). He is a Highly Cited Researcher in both Engineering and Computer Science (Clarivate Analytics). He has served as an AdCom Member of IEEE Industrial Electronics Society (IES), a Member of IEEE IES Fellows Committee, and Chair of IEEE IES Technical Committee on Networked Control Systems. Currently, he is Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica, Co-Editor-in-Chief of IEEE Transactions on Industrial Informatics, and Co-Editor of Australian Journal of Electrical and Electronic Engineering
Corresponding author: Qing-Long Han, e-mail: qhan@swin.edu.au
Received Date: 2021-11-15
Revised Date: 2021-12-30
Accepted Date: 2022-01-13

Available Online: 2022-03-16

Abstract

Abstract

This paper is concerned with the cooperative target tracking of multiple autonomous surface vehicles (ASVs) under switching interaction topologies. For the target to be tracked, only its position can be measured/received by some of the ASVs, and its velocity is unavailable to all the ASVs. A distributed extended state observer taking into consideration switching topologies is designed to integrally estimate unknown target dynamics and neighboring ASVs’ dynamics. Accordingly, a novel kinematic controller is designed, which takes full advantage of known information and avoids the approximation of some virtual control vectors. Moreover, a disturbance observer is presented to estimate unknown time-varying environmental disturbance. Furthermore, a distributed dynamic controller is designed to regulate the involved ASVs to cooperatively track the target. It enables each ASV to adjust its forces and moments according to the received information from its neighbors. The effectiveness of the derived results is demonstrated through cooperative target tracking performance analysis for a tracking system composed of five interacting ASVs.
- Autonomous surface vehicles (ASVs),
- cooperative target tracking,
- distributed extended state observer,
- switching topologies

FullText(HTML)

References(47)

References

[1]	T. I. Fossen, Handbook of Marine Craft Hydrodynamics and Motion Control. Chichester, UK: Wiley, 2011.
[2]	Y.-L. Wang and Q.-L. Han, “Network-based modelling and dynamic output feedback control for unmanned marine vehicles,” Automatica, vol. 91, pp. 43–53, May 2018. doi: 10.1016/j.automatica.2018.01.026
[3]	Z. Du, R. R. Negenborn, and V. Reppa, “Cooperative multi-agent control for autonomous ship towing under environmental disturbances,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 8, pp. 1365–1379, Aug. 2021. doi: 10.1109/JAS.2021.1004078
[4]	C. Lv, H. Yu, J. Chi, T. Xu, H. Zang, H. Jiang, and Z. Zhang, “A hybrid coordination controller for speed and heading control of underactuated unmanned surface vehicles system,” Ocean Eng., vol. 176, pp. 222–230, Mar. 2019. doi: 10.1016/j.oceaneng.2019.02.007
[5]	Z. Gao and G. Guo, “Command filtered finite/fixed-time heading tracking control of surface vehicles,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 10, pp. 1667–1676, Oct. 2021. doi: 10.1109/JAS.2021.1004135
[6]	Y.-L. Wang, Q.-L. Han, M. Fei, and C. Peng, “Network-based T-S fuzzy dynamic positioning controller design for unmanned marine vehicles,” IEEE Trans. Cybern., vol. 48, no. 9, pp. 2750–2763, Sept. 2018. doi: 10.1109/TCYB.2018.2829730
[7]	J. Du, X. Hu, M. Krstić, and Y. Sun, “Robust dynamic positioning of ships with disturbances under input saturation,” Automatica, vol. 7, pp. 207–214, Nov. 2016.
[8]	L. Ma, Y.-L. Wang, and Q.-L. Han, “Event-triggered dynamic positioning for mass-switched unmanned marine vehicles in network environments,” IEEE Trans. Cybern., vol. 52, no. 5, pp. 3159–3171, May 2022. doi: 10.1109/TCYB.2020.3008998
[9]	J. Ye, S. Roy, M. Godjevac, V. Reppa, and S. Baldi, “Robustifying dynamic positioning of crane vessels for heavy lifting operation,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 753–765, Apr. 2021. doi: 10.1109/JAS.2021.1003913
[10]	M. Breivik, V. E. Hovstein, and T. I. Fossen, “Straight-line target tracking for unmanned surface vehicles,” Model.,Identificat. Control, vol. 29, no. 4, pp. 131–149, 2008. doi: 10.4173/mic.2008.4.2
[11]	L. Liu, D. Wang, Z. Peng, C. L. P. Chen, and T. Li, “Bounded neural network control for target tracking of underactuated autonomous surface vehicles in the presence of uncertain target dynamics,” IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 4, pp. 1241–1249, Apr. 2019. doi: 10.1109/TNNLS.2018.2868978
[12]	S. Gao, Z. Peng, L. Liu, H. Wang, and D. Wang, “Coordinated target tracking by multiple unmanned surface vehicles with communication delays based on a distributed event-triggered extended state observer”, Ocean Eng., vol. 227, p. 108283, May 2021.
[13]	Y. Yang, J. Du, H. Liu, C. Guo, and A. Abraham, “A trajectory tracking robust controller of surface vessels with disturbance uncertainties,” IEEE Trans. Control Syst. Technol., vol. 22, no. 4, pp. 1511–1518, Jul. 2014. doi: 10.1109/TCST.2013.2281936
[14]	S. Dai, S. He, M. Wang, and C. Yuan, “Adaptive neural control of underactuated surface vessels with prescribed performance guarantees,” IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 12, pp. 3686–3698, Dec. 2019. doi: 10.1109/TNNLS.2018.2876685
[15]	Z. Zheng, L. Sun, and L. Xie, “Error-constrained LOS path following of a surface vessel with actuator saturation and faults,” IEEE Trans. Syst.,Man,Cybern.,Syst., vol. 48, no. 10, pp. 1794–1804, Oct. 2018. doi: 10.1109/TSMC.2017.2717850
[16]	L. Liu, D. Wang, and Z. Peng, “ESO-based line-of-sight guidance law for path following of underactuated marine surface vehicles with exact sideslip compensation,” IEEE J. Ocean. Eng., vol. 42, no. 2, pp. 477–487, Apr. 2017. doi: 10.1109/JOE.2016.2569218
[17]	C. Liu, D. Wang, Y. Zhang, and X. Meng, “Model predictive control for path following and roll stabilization of marine vessels based on neurodynamic optimization,” Ocean Eng., vol. 217, Dec. 2020.
[18]	Z. Peng, J. Wang, D. Wang, and Q.-L. Han, “An overview of recent advances in coordinated control of multiple autonomous surface vehicles,” IEEE Trans. Ind. Informat., vol. 17, no. 2, pp. 732–745, Feb. 2021. doi: 10.1109/TII.2020.3004343
[19]	O. Elhaki and K. Shojaei, “Neural network-based target tracking control of underactuated autonomous underwater vehicles with a prescribed performance,” Ocean Eng., vol. 167, pp. 239–256, Nov. 2018. doi: 10.1016/j.oceaneng.2018.08.007
[20]	O. Namaki-Shoushtari, A. P. Aguiar, and A. Khaki-Sedigh, “Target tracking of autonomous robotic vehicles using range-only measurements: a switched logic-based control strategy,” Int. J. Robust Nonlinear Control, vol. 22, no. 17, p. 1983C1998, Nov. 2011.
[21]	K. Shojaei, “Three-dimensional neural network tracking control of a moving target by underactuated autonomous underwater vehicles,” Neural Comput. Appl., vol. 31, pp. 509–521, Feb. 2019.
[22]	K. Choi, S. J. Yoo, J. B. Park, and Y. H. Choi, “Adaptive formation control in absence of leader’s velocity information,” IET Control Theory Appl., vol. 4, no. 4, pp. 521–528, Apr. 2010. doi: 10.1049/iet-cta.2009.0074
[23]	Z. Peng and D. Wang, “Robust adaptive formation control of autonomous surface vehicles with uncertain dynamics,” IET Control Theory Appl., vol. 5, no. 12, pp. 1378–1387, Aug. 2011. doi: 10.1049/iet-cta.2010.0429
[24]	R. Cui, S. S. Ge, B. V. E. How, and Y. S. Choo, “Leader-follower formation control of underactuated autonomous underwater vehicles,” Ocean Eng., vol. 37, no. 17−18, pp. 1491–1502, Dec. 2010. doi: 10.1016/j.oceaneng.2010.07.006
[25]	L. Ma, Y.-L. Wang, and Q.-L. Han, “H_∞ cluster formation control of networked multiagent systems with stochastic sampling,” IEEE Trans. Cybern., vol. 51, no. 12, pp. 5761–5772, Dec. 2021. doi: 10.1109/TCYB.2019.2959201
[26]	Y. Yang and D. Yue, “Distributed tracking control of a class of multi-agent systems in non-affine pure-feedback form under a directed topology,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 169–180, Jan. 2018. doi: 10.1109/JAS.2017.7510382
[27]	X. Ge, Q.-L. Han, L. Ding, Y.-L. Wang, and X.-M. Zhang, “Dynamic event-triggered distributed coordination control and its applications: A survey of trends and techniques,” IEEE Trans. Syst.,Man,Cybern.,Syst., vol. 50, no. 9, pp. 3112–3125, Sept. 2020. doi: 10.1109/TSMC.2020.3010825
[28]	Y. Wang, Y. Liu, and Z. Wang, “Theory and experiments on enclosing control of multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 10, pp. 1677–1685, Oct. 2021. doi: 10.1109/JAS.2021.1004138
[29]	W. Hu, L. Liu, and G. Feng, “Output consensus of heterogeneous linear multi-agent systems by distributed event-triggered/self-triggered strategy,” IEEE Trans. Cybern., vol. 47, no. 8, pp. 1914–1924, Aug. 2017. doi: 10.1109/TCYB.2016.2602327
[30]	X. Ge, Q.-L. Han, J. Wang, and X.-M. Zhang, “A scalable adaptive approach to multi-vehicle formation control with obstacle avoidance,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 6, pp. 990–1004, Jun. 2022. doi: 10.1109/JAS.2021.1004263
[31]	B. Xiao, X. Yang, and X. Huo, “A novel disturbance estimation scheme for formation control of ocean surface vessels,” IEEE Trans. Ind. Electron., vol. 64, no. 6, pp. 4994–5003, Jun. 2017. doi: 10.1109/TIE.2016.2622219
[32]	T. Li, R. Zhao, C. L. P. Chen, L. Fang, and C. Liu, “Finite-time formation control of under-actuated ships using nonlinear sliding mode control,” IEEE Trans. Cybern., vol. 48, no. 11, pp. 3243–3253, Nov. 2018. doi: 10.1109/TCYB.2018.2794968
[33]	Z. Peng, J. Wang, and D. Wang, “Distributed maneuvering of autonomous surface vehicles based on neurodynamic optimization and fuzzy approximation,” IEEE Trans. Control Syst. Technol., vol. 26, no. 3, pp. 1083–1090, May 2018. doi: 10.1109/TCST.2017.2699167
[34]	X. Dong, Y. Zhou, Z. Ren, and Y. Zhong, “Time-varying formation tracking for second-order multi-agent systems subjected to switching topologies with application to quadrotor formation flying,” IEEE Trans. Ind. Electron., vol. 64, no. 6, pp. 5014–5024, Jun. 2017. doi: 10.1109/TIE.2016.2593656
[35]	J. Dai and G. Guo, “Event-triggered leader-following consensus for multi-agent systems with semi-Markov switching topologies,” Inf. Sci., vol. 459, pp. 290–301, Aug. 2018. doi: 10.1016/j.ins.2018.04.054
[36]	Y. Cheng, Y. Zhang, L. Shi, J. Shao, and Y. Xiao, “Consensus seeking in heterogeneous second-order multi-agent systems with switching topologies and random link failures,” Neurocomputing, vol. 319, pp. 188–195, Nov. 2018. doi: 10.1016/j.neucom.2018.08.051
[37]	M. Meng, G. Xiao, C. Zhai, G. Li, and Z. Wang, “Distributed consensus of heterogeneous multi-agent systems subject to switching topologies and delays,” J. Frankl. Inst., vol. 357, no. 11, pp. 6899–6917, Jul. 2020. doi: 10.1016/j.jfranklin.2020.04.045
[38]	R. Cui, L. Chen, C. Yang, and M. Chen, “Extended state observer-based integral sliding mode control for an underwater robot with unknown disturbances and uncertain nonlinearities,” IEEE Trans. Ind. Electron., vol. 64, no. 8, pp. 6785–6795, Aug. 2017. doi: 10.1109/TIE.2017.2694410
[39]	J. Zhang, S. Yu, and Y. Yan, “Fixed-time extended state observer-based trajectory tracking and point stabilization control for marine surface vessels with uncertainties and disturbances,” Ocean Eng., vol. 186, p. 106109, Aug. 2019.
[40]	Q. Song, F. Liu, J. Cao, and W. Yu, “M-matrix strategies for pinning-controlled leader-following consensus in multiagent systems with non-linear dynamics,” IEEE Trans. Cybern., vol. 43, no. 6, pp. 1688–1697, Dec. 2013. doi: 10.1109/TSMCB.2012.2227723
[41]	J. P. Hespanha and A. S. Morse, “Stability of switched systems with average dwell-time,” in Proc. 38th IEEE Conf. Decis. Control, Dec. 1999, pp. 2655–2660.
[42]	L. Zou, Z. Wang, J. Hu, and D. Zhou, “Moving horizon estimation with unknown inputs under dynamic quantization effects,” IEEE Trans. Autom. Control, vol. 65, no. 12, pp. 5368–5375, Dec. 2020. doi: 10.1109/TAC.2020.2968975
[43]	L. Zou, Z. Wang, J. Hu, and H. Dong, “Ultimately bounded filtering subject to impulsive measurement outliers,” IEEE Trans. Autom. Control, vol. 67, no. 1, pp. 304–319, Jan. 2022. doi: 10.1109/TAC.2021.3081256
[44]	L. Zou, Z. Wang, Q.-L. Han, and D. Yue, “Tracking control under round-robin scheduling: Handling impulsive transmission outliers,” IEEE Trans. Cybern., DOI: 10.1109/TCYB.2021.3115459.
[45]	R. Skjetne, T. I. Fossen, and P. V. Kokotović, “Adaptive maneuvering, with experiments, for a model ship in a marine control laboratory,” Automatica, vol. 41, no. 2, pp. 289–298, Feb. 2005. doi: 10.1016/j.automatica.2004.10.006
[46]	C. Gao, Z. Wang, X. He, and Q.-L. Han, “Consensus control of linear multiagent systems under actuator imperfection: When saturation meets fault,” IEEE Trans. Syst.,Man,Cybern.,Syst., vol. 52, no. 4, pp. 2651–2663, Apr. 2022. doi: 10.1109/TSMC.2021.3050370
[47]	C. Gao, Z. Wang, X. He, and D. Yue, “Sampled-data-based fault-tolerant consensus control for multi-agent systems: A data privacy preserving scheme,” Automatica, vol. 133, p. 109847, Nov. 2021.

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(9)

Get Citation

PDF

XML

Article Metrics

Article views (799) PDF downloads(144)

Highlights

For the target to be tracked, only its position can be measured/received by some of the ASVs, and its velocity is unavailable to all the ASVs, a distributed extended state observer is designed to integrally estimate unknown target dynamics and neighboring ASVs' dynamics
A novel kinematic controller is designed, which takes full advantage of known information and avoids the approximation of some virtual control vectors
A disturbance observer is presented to estimate unknown time-varying environmental disturbance
A distributed dynamic controller is designed to regulate the involved ASVs to cooperatively track the target. It enables each ASV to adjust its forces and moments according to the received information from its neighbors

Cooperative Target Tracking of Multiple Autonomous Surface Vehicles Under Switching Interaction Topologies

doi: 10.1109/JAS.2022.105509

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Highlights

Export File

Citation

Format

Content