Hostname: page-component-7b7567c8c-fvjsw Total loading time: 0 Render date: 2026-11-15T11:18:22.718Z Has data issue: false hasContentIssue false
  • English
  • Français

Cooperative Pursuit Control for Multiple Underactuated Underwater Vehicles with Time Delay in Three-Dimensional Space

Published online by Cambridge University Press:  27 October 2020

Xue QiOpen the ORCID record for Xue Qi[Opens in a new window] and
Zhi-Jun Cai
Xue Qi*
Affiliation:
College of Information and Network Engineering, Anhui Science and Technology University, Fengyang 233100, China
Zhi-Jun Cai
Affiliation:
School of Finance and Economics, Anhui Science and Technology University, Fengyang 233100, China
*
*Corresponding author. E-mail: qixuesnow@163.com
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

In this paper, the k-valued logic control network is introduced to study the cooperative pursuit control problem of multiple underactuated underwater vehicles (UUVs) with time delay in three-dimensional space. The semi-tensor product of matrices is used to solve the complex calculation problem of the large dimension matrix. The influence of communication delay on multiple UUVs’ optimization and cooperative pursuit control is expressed in a matrix. Under the leadership of evader UUV, the control algorithm can ensure that all the pursuit UUVs reach the desired position. The stability of the closed loop system is proved.

Keywords

Underactuated underwater vehiclek-valued logic control networksCoordinated controlTime delayPursuit control93C8593B5165P40

Information

Type
Article
Information
Robotica , Volume 39 , Issue 6 , June 2021, pp. 1101 - 1115
Copyright
© The Author(s), 2020. Published by Cambridge University Press

References

Shah, K., Schwager, M.. “Multi-agent cooperative pursuit-evasion strategies under uncertainty,” Generalized Models and Non-classical Approaches in Complex Materials 2, (2019).Google Scholar
Qi, X., Xiang, P.. “Coordinated path following control of multiple underactuated underwater vehicles,” Proceedings of the 37th Chinese Control Conference, 7.25–7.27, 6633–6638 (2018).CrossRefGoogle Scholar
Qi, X.. “Coordinated control for multiple underactuated underwater vehicles with time delay in game theory frame,” Proceedings of the 36th Chinese Control Conference, 7.26–7.28, 8419–8424 (2017).Google Scholar
Khan, A., Rinner, B., Cavallaro, A., “Cooperative robots to observe moving targets: Review,” IEEE Trans Cyber. 48(1), 187–198 (2017).CrossRefGoogle Scholar
Wan, S., Lu, J., Fan, P.. “Semi-centralized control for multi robot formation,” International Conference on Robotics & Automation Engineering. IEEE, (2018).CrossRefGoogle Scholar
Boubou, S., Asl, H. J., Narikiyo, T., Kawanishi, M.. “Real-time recognition and pursuit in robots based on 3D depth data,” J Intell Robot Syst. 6, 1–14 (2018).Google Scholar
Murray, R. M., “Recent research in cooperative control of multivehicle systems,” Trans ASME J Dyn Syst Measure Control 129(5), 571–598 (2007).CrossRefGoogle Scholar
Zhang, P., Yang, T.. “Formation Path-following of Multiple Underwater Vehicles Based on Fault Tolerant Control and Port-controlled Hamiltonian systems,” The 30th Chinese Control and Decision Conference (2018).Google Scholar
Liu, T., Jiang, Z. P., “Distributed formation control of nonholonomic mobile robots without global position measurements,” Automatica 49(2), 592–600 (2013).CrossRefGoogle Scholar
Durr, H. B., Stankovic, M. S., Johansson, K. H., “Distributed positioning of autonomous mobile sensors with application to coverage control,” American Control Conference (2011) pp. 12–18.Google Scholar
Zhu, M., Otte, M., Chaudhari, P., Frazzoli, E., “Game theoretic controller synthesis for multi-robot motion planning Part I: Trajectory based algorithms,” Proceedings-IEEE International Conference on Robotics and Automation, (2014) pp. 1–7.Google Scholar
Zhang, D., Li, J., Hui, D.. “Coordinated control for voltage regulation of distribution network voltage regulation by distributed energy storage systems,” Protect Control Modern Power Syst. 3(1), 3 (2018).CrossRefGoogle Scholar
Zuhair, Q. M., Songhao, P., Haiyang, J., Mohammed, E. H. S.. “A novel approach for multi-agent cooperative pursuit to capture grouped evaders,” J Supercomput. 12(1), 46–53 (2018).Google Scholar
Galloway, K. S., Dey, B., “Beacon-referenced Mutual Pursuit in Three Dimensions,” IEEE 2018 Annual American Control Conference (ACC) (2018) pp. 62–67.Google Scholar
Khan, A., Rinner, B., Cavallaro, A., “Cooperative robots to observe moving targets: Review,” IEEE Trans Cybern. 48(1), 187–198 (2017).CrossRefGoogle Scholar
Chen, M., Zhu, D., “A novel cooperative hunting algorithm for inhomogeneous multiple autonomous underwater vehicles,” IEEE Access 6(99), 7818–7828 (2018).CrossRefGoogle Scholar
Qi, X., Xiang, P., Cai, Z. J.. “Three-dimensional consensus control based on learning game theory for multiple underactuated underwater vehicles,” Ocean Eng. 188, 106–201 (2019).CrossRefGoogle Scholar
Qi, X., Cai, Z. J.. “Three-dimensional formation control based on nonlinear small gain method for multiple underactuated underwater vehicles,” Ocean Eng. 151, 105–114 (2018).CrossRefGoogle Scholar
Qi, X., Cai, Z. J.. “Three-dimensional formation control based on filter backstepping method for multiple underactuated underwater vehicles,” Robotica 35(8), 1690–1711 (2017).CrossRefGoogle Scholar
Zhao, Y., Li, Z., Cheng, D., “Optimal control of logical control networks,” IEEE Trans Autom Control. 56(56), 1766–1776 (2011).CrossRefGoogle Scholar
Cheng, D., Zhao, Y., Xu, X., “Mix-valued logic and its applications,” J Shandong Univ. 46(10), 32-44 (2011).Google Scholar