logo

SCIENTIA SINICA Informationis, Volume 50 , Issue 3 : 408-423(2020) https://doi.org/10.1360/SSI-2019-0171

Distributed time-varying group formation tracking for cluster systems under switching topologies

More info
  • ReceivedAug 16, 2019
  • AcceptedSep 17, 2019
  • PublishedFeb 28, 2020

Abstract

Distributed formation control is one of the basic important subjects of cluster intelligent control. Denial environments and multi-task requirements present new challenges to formation control. This paper investigates the time-varying group formation tracking control problem for high-order linear cluster systems. It divides the agents in the cluster systems into three classes: the virtual leader, the group leaders, and the followers. The virtual leader provides reference trajectories or tracking instructions for the macro-movement of the cluster systems. The group leaders track these trajectories and instructions and ensure the coordination among the subgroups by communicating with each other. The followers track the state of the subgroup leaders and realize the desired formation. Under switching topologies and external disturbances, a distributed time-varying group formation tracking control protocol is constructed based on the neighboring information feedback among agents and the sliding mode control theory, and an algorithm is proposed to determine the unknown parameters of this protocol. Then, the closed-loop stability of such cluster systems is proven by using the Lyapunov theory. Finally, numerical simulations demonstrate that the proposed approach can achieve time-varying group formation tracking for high-order linear cluster systems.


Funded by

国家自然科学基金(61873011,61803014)

北京市自然科学基金(4182035)


References

[1] Ray R J, Cobleigh B R, Vachon M J. Flight test techniques used to evaluate performance benefits during formation flight. In: Proceedings of AIAA Atmospheric Flight Mechanics Conference and Exhibit, 2002. 4492. Google Scholar

[2] Zhong Q, Wang D D, Shao S K, et al. Research status and development of muli UAV coordinated formation flight control. Journal of Harbin Institute of Technology, 2017, 49: 1--14. Google Scholar

[3] Desai J P, Ostrowski J P, Kumar V. Modeling and control of formations of nonholonomic mobile robots. IEEETrans Robot Autom, 2001, 17: 905--908. Google Scholar

[4] Lewis M A, Tan K H. Autonomous Robots, 1997, 4: 387-403 CrossRef Google Scholar

[5] Balch T, Arkin R C. Behavior-based formation control for multirobot teams. IEEE Trans Robot Automat, 1998, 14: 926-939 CrossRef Google Scholar

[6] Beard R W, Lawton J, Hadaegh F Y. A coordination architecture for spacecraft formation control. IEEE Trans Contr Syst Technol, 2001, 9: 777-790 CrossRef Google Scholar

[7] Takahashi H, Nishi H, Ohnishi K. Autonomous Decentralized Control for Formation of Multiple Mobile Robots Considering Ability of Robot. IEEE Trans Ind Electron, 2004, 51: 1272-1279 CrossRef Google Scholar

[8] Ren W. Consensus strategies for cooperative control of vehicle formations. IET Control Theor Appl, 2007, 1: 505-512 CrossRef Google Scholar

[9] Dong X W, Hu G Q. Time-varying formation control for general linear multi-agent systems with switching directed topologies. Automatica, 2016, 73: 47-55 CrossRef Google Scholar

[10] Wang R, Dong X W, Li Q D. Distributed Adaptive Formation Control for Linear Swarm Systems With Time-Varying Formation and Switching Topologies. IEEE Access, 2016, 4: 8995-9004 CrossRef Google Scholar

[11] Hua Y Z, Dong X W, Li Q D, et al. Robust adaptive time-varying formation control for high-order linear uncertain multi-agent systems. In: Proceedings of 2017 36th Chinese Control Conference (CCC), Dalian, 2017. 8349--8354. Google Scholar

[12] Yu J L, Dong X W, Li Q D, et al. Distributed time-varying formation control for second-order nonlinear multi-agent systems based on observers. In: Proceedings of 2017 29th Chinese Control And Decision Conference (CCDC), Chongqing, 2017. 6313--6318. Google Scholar

[13] Xiao W, Yu J L, Wang R. Time-Varying Formation Control for Time-Delayed Multi-Agent Systems with General Linear Dynamics and Switching Topologies. Un Sys, 2019, 07: 3-13 CrossRef Google Scholar

[14] Dong X W, Zhou Y, Ren Z. Time-Varying Formation Tracking for Second-Order Multi-Agent Systems Subjected to Switching Topologies With Application to Quadrotor Formation Flying. IEEE Trans Ind Electron, 2017, 64: 5014-5024 CrossRef Google Scholar

[15] Yu J L, Dong X W, Li Q D. Practical Time-Varying Formation Tracking for Second-Order Nonlinear Multiagent Systems With Multiple Leaders Using Adaptive Neural Networks.. IEEE Trans Neural Netw Learning Syst, 2018, 29: 6015-6025 CrossRef PubMed Google Scholar

[16] Li X D, Dong X W, Li Q D, et al. Time-varying formation tracking control for multi-agent systems with input saturation. In: Proceedings of 2017 36th Chinese Control Conference (CCC), Dalian, 2017. 8737--8742. Google Scholar

[17] Yu J L, Dong X W, Li Q D, et al. Robust $H_{\infty}$ guaranteed cost time-varying formation tracking for high-order multiagent systems with time-varying delays. IEEE Trans Syst Man Cybern Syst, 2018. doi: 10.1109/TSMC.2018.2883516. Google Scholar

[18] Hua Y Z, Dong X W, Han L, et al. Finite-time time-varying formation tracking for high-order multiagent systems with mismatched disturbances. IEEE Trans Syst Man Cybern Syst, 2018. doi: 10.1109/TSMC.2018.2867548. Google Scholar

[19] Dong X, Li Q, Zhao Q. Time-varying group formation analysis and design for second-order multi-agent systems with directed topologies. Neurocomputing, 2016, 205: 367-374 CrossRef Google Scholar

[20] Li Y F, Dong X W, Li Q D, et al. Time-varying group formation control for second-order multi-agent systems with switching directed topologies. In: Proceedings of 2017 36th Chinese Control Conference (CCC), Dalian, 2017. 8530--8535. Google Scholar

[21] Wang F Y, Yang H Y, Zhang S N. Containment Control for First-Order Multi-Agent Systems with Time-Varying Delays and Uncertain Topologies. Commun Theor Phys, 2016, 66: 249-255 CrossRef ADS Google Scholar

[22] Li Z K, Duan Z S, Chen G R. Consensus of Multiagent Systems and Synchronization of Complex Networks: A Unified Viewpoint. IEEE Trans Circuits Syst I, 2010, 57: 213-224 CrossRef Google Scholar

[23] Tian L. The control of unmanned aerial vehicle based on PID and LESO. Navigation Positioning & Timing, 2018, 5: 41--46. Google Scholar

Copyright 2020  CHINA SCIENCE PUBLISHING & MEDIA LTD.  中国科技出版传媒股份有限公司  版权所有

京ICP备14028887号-23       京公网安备11010102003388号