Skip to main content
SpringerLink
Log in

Observer-Based Adaptive Consensus for Multi-agent Systems with Nonlinear Dynamics

  • Conference paper
  • First Online:
Proceedings of the 2015 Chinese Intelligent Systems Conference

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

Abstract

Distributed consensus problem is investigated for Lipschitz nonlinear multi-agent systems (MASs). Under the assumption that the states of the multiple agents are unmeasured, nonlinear observer for each agent is designed. Based on these observers, a distributed protocol is proposed, in which the coupling weights between adjacent agents are time-varying and can automatically change according to the designed adaptive law. Lyapunov-Krasovskii functional is constructed to analyses the consensus problem of the MASs under the proposed distributed adaptive protocol. By using free-weighting matrix approach, sufficient conditions that can ensure consensus are given. Finally, numerical example is presented to illustrate our result.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Su H, Wang X, Lin Z (2009) Flocking of multi-agents with a virtual leader. Control Theory Appl 54(2):293–307

    MathSciNet  Google Scholar 

  2. Wang Y, Yan W (2013) Consensus formation tracking control of multiple autonomous underwater vehicle system. J Guid Control Dyn 30(3):380–384

    MathSciNet  Google Scholar 

  3. Zhang T, Yu H (2010) Average consensus for directed networks of multi-agent with time-varying delay. In: Advances in swarm intelligence, Beijing, Chian, pp. 723–730

    Google Scholar 

  4. Ren W, Beard R (2005) Consensus seeking in multi-agent systems under dynamically changing interaction topologies. IEEE Trans Autom Control 50(5):655–661

    Article  Google Scholar 

  5. Lin P, Jia Y (2008) Distributed robust \(H_{\infty }\) consensus control in directed networks of agents with time-delay. Syst Control Lett 57(8):643–653

    Article  MathSciNet  MATH  Google Scholar 

  6. Olfati-Saber R, Murray RM (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 

  7. Ren W, Beard R, Atkins E (2005) A survey of consensus problem in multi-agent coordination. In: Proceedings of the american control conference, pp 1859–1864. IEEE, Portland

    Google Scholar 

  8. Olfati-Saber R, Fax JA, Murry RM (2007) Consensus and cooperation in networked multi-agent systems. Proc IEEE 95(1):215–233

    Article  Google Scholar 

  9. Li Z, Duan Z, Chen G, Huang L (2010) Consensus of multi-agent systems and synchronization of complex networks: a unified viewpoint. Circuits Syst I Regul Pap IEEE Trans 57(1):213–224

    Article  MathSciNet  Google Scholar 

  10. Seo JH, Shim H, Back J (2009) Consensus of high-order linear systems using dynamic output feedback compensator: low gain approach. Automatica 45(11):2659–2664

    Article  MathSciNet  MATH  Google Scholar 

  11. DeLellis P, Bernardo M, Garofalo F (2009) Novel decentralized adaptive strategies for the synchronization of complex networks. Automatica 45(5):1312–1319

    Article  MathSciNet  MATH  Google Scholar 

  12. Hong Y, Wang X, Jiang Z (2013) Distributed output regulation of leader-follower multi-agent systems. Int J Robust Nonlinear Control 23(1):48–66

    Article  MathSciNet  MATH  Google Scholar 

  13. Hu J, Cao J, Yu J et al (2014) Consensus of nonlinear multi-agent systems with observer-based protocols. Syst Control Lett 72:71–79

    Article  MathSciNet  MATH  Google Scholar 

  14. Li Z, Ren W, Liu X, Fu M (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 

  15. De Oliveira MC, Bernussou J, Geromel JC (1999) A new discrete-time robust stability condition. Syst Control Lett 37(4):261–265

    Google Scholar 

Download references

Acknowledgments

This paper was supported by National Natural Science Foundation (61203143), and Hujiang Foundation of China (C14002).

Author information

Authors and Affiliations

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

    Heyang Wang & Lin Li

Authors
  1. Heyang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lin Li .

Editor information

Editors and Affiliations

  1. Beihang University, Beijing, China

    Yingmin Jia

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

    Junping Du

  3. Tsinghua University, Beijing, China

    Hongbo Li

  4. University of Science & Technology Beijing, Beijing, China

    Weicun Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, H., Li, L. (2016). Observer-Based Adaptive Consensus for Multi-agent Systems with Nonlinear Dynamics. In: Jia, Y., Du, J., Li, H., Zhang, W. (eds) Proceedings of the 2015 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48365-7_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-48365-7_29

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48363-3

  • Online ISBN: 978-3-662-48365-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation