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Observer-Based Leader Following Consensus of Nonlinear Multi-agent Systems with a Leader of Bounded Input

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Proceedings of 2019 Chinese Intelligent Systems Conference (CISC 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 593))

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Abstract

The leader-following consensus of multi-agent systems with Lipschitz nonlinear dynamics and a leader of bounded input is investigated in this paper. Firstly, for dealing with the difficult measurement of the real-time states, an state observer is designed for each agent. Considered the bounded input of leader, a consensus control protocol is proposed for the multi-agent systems. Then, the validity of the control protocol is proved by Lyapunov stability theory and graph theory. Finally, a numerical example is given to demonstrate the effectiveness of the control protocol.

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References

  1. Olfati-Saber R, Murray R (2004) Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans Autom Control 49(9):1520–1533

    Article  MathSciNet  Google Scholar 

  2. Fax JA, Murray RM (2004) Information flow and cooperative control of vehicle formations. IEEE Trans Autom Control 49(9):1465–1476

    Article  MathSciNet  Google Scholar 

  3. Olfati-Saber R, Murray R (2003) Consensus protocols for networks of dynamic agents. In: American control conference, June, vol 2, pp 951–956

    Google Scholar 

  4. Ren W, Beard RW (2007) Information consensus in multivehicle cooperative control. IEEE Control Syst Mag 1066-033x

    Google Scholar 

  5. Ren W, Atkins EM (2007) Distributed multi-vehicle coordinated control via local information exchange. Int J Robust Nonlinear Control 17(1011):1002–1033

    Article  MathSciNet  Google Scholar 

  6. Li ZK, Liu XD (2012) Distributed tracking control for linear multi-agent systems with a leader of bounded input using output information. In: Proceedings of the 10th world congress on intelligent control and automation, Beijing, China, pp 1756–1761

    Google Scholar 

  7. Yang YB, Wang CL (2013) Obstacle avoidance method for mobile robots based on improved artificial potential field method and its implementation on MATLAB. J Univ Shanghai Sci Technol 35(5):496–500

    Google Scholar 

  8. Li ZK, Ren W, Liu XD (2013) Distributed consensus of linear multi-agent systems with adaptive dynamics protocol. Automatica 49:1986–1995

    Article  MathSciNet  Google Scholar 

  9. Cheng TH, Kan Z, Shea JM, Dixion WE (2009) Decentralized event-triggered control for leader-follower consensus. In: The 53rd IEEE conference on decision and control, Los Angeles, USA, pp 1244–1249

    Google Scholar 

  10. Li ZK, Wen GH, Duan ZS (2014) Designing fully distributed consensus protocols for linear multi-agent systems with directed graphs. IEEE Trans Autom Control 60:1152–1157

    Article  MathSciNet  Google Scholar 

  11. Tanner H, Jadbabalie A, Pappas G (2007) Flocking in fixed and switching networks. IEEE Trans Autom Control 52(5):863–868

    Article  MathSciNet  Google Scholar 

  12. Li ZK, Ren W, Liu XD (2013) Consensus of multi-agent systems with general linear and Lipschitz nonlinear dynamics using distributed adaptive protocols. IEEE Trans Autom Control 58(7):1786–1791

    Article  MathSciNet  Google Scholar 

  13. Meng XY, Chen TW (2013) Event based agreement protocols for multi-agent networks. Automatica 49(7):2125–2132

    Article  MathSciNet  Google Scholar 

  14. Zhang H, Feng G, Yan HC (2014) Observer-based output feedback event-triggered control for consensus of multi-agent systems. IEEE Trans Ind Electron 61(9):4885–4894

    Article  Google Scholar 

  15. Zhou B, Liao XF, Huang TW (2015) Leader-following exponential consensus of general linear multi-agent systems via event-triggered control with combinational measurements. Appl Math Lett 40(2):35–41

    Article  MathSciNet  Google Scholar 

  16. Deng C, Yang GH (2019) Leaderless and leader-following consensus of linear multi-agent systems with distributed event-triggered estimators. J Franklin Inst 356(1):309–311

    Article  MathSciNet  Google Scholar 

  17. Dimarogonas DV, Frazzoli E, Johansson KH (2012) Distributed event-triggered control for multi-agent systems. IEEE Trans Autom Control 57(5):1291–1297

    Article  MathSciNet  Google Scholar 

  18. Miao W, Zhang H, Yan H, Ren H (2016) Self-triggered output feedback control for consensus of multi-agent systems. Neurocomputing 190:179–187

    Article  Google Scholar 

  19. Zhang H, Feng G, Yan H, Chen Q (2014) Distributed self-triggered control for consensus of multi-agent systems. IEEE/CAA J Autom Sinica 1(1):40–45

    Article  Google Scholar 

  20. Shi Y, Yin YY (2017) Distributed leader-following consensus of a class of nonlinear multi-agent systems. In: 11th Asian control conference. Gold Coast Convention Centre, Australia

    Google Scholar 

  21. Zhang XX, Liu XP (2017) Consensus of linear multi-agent systems with disturbance generated from heterogeneous nonlinear exosystems. In: Proceedings of the 36th Chinese control conference, Dalian, China, pp 8063–8067

    Google Scholar 

  22. Zou WC, Guo J, Xiang ZR (2018) Leader-following consensus protocol design of second-order nonlinear multi-agent systems with unmodeled dynamics. In: Proceedings of the 37th Chinese control conference, Wuhan, China, pp 6884–6889

    Google Scholar 

  23. Lu J, Li L (2018) Leader-following consensus of nonlinear multi-agent systems using observer-based event-triggered control. In: 5th international conference on information, cybernetics and computational social systems, Hangzhou, China, pp 247–252

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Ziyi Wang & Lin Li

Authors
  1. Ziyi Wang
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  2. Lin Li
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Corresponding author

Correspondence to Lin Li .

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Editors and Affiliations

  1. Beihang University, Beijing, China

    Yingmin Jia

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

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Wang, Z., Li, L. (2020). Observer-Based Leader Following Consensus of Nonlinear Multi-agent Systems with a Leader of Bounded Input. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2019 Chinese Intelligent Systems Conference. CISC 2019. Lecture Notes in Electrical Engineering, vol 593. Springer, Singapore. https://doi.org/10.1007/978-981-32-9686-2_48

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