Skip to main content
SpringerLink
Log in

Quantized Consensus of Multi-agent Systems with Additive Noise

  • Conference paper
  • First Online:
Book cover Intelligent Robotics and Applications (ICIRA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9834))

Included in the following conference series:

Abstract

This paper investigates the average consensus problem of multiple discrete-time integrator agents under communication constraints and additive noise. In real applications, both quantization error and additive noise are often unavoidable and may terribly degrade the consensus performance. To handle quantization, we adopt a distributed dynamic encoding and decoding policy, under which the resolution of quantizers can change over time to tightly catch up the states and provide more accurate information. Moreover, bounded additive noise is considered. By generalizing the original noise-free protocol in [14], we propose a modified protocol with a new scaling function and prove that under our protocol, one can achieve approximate consensus even with 1 bit per channel use under the perturbation of additive noise. Furthermore we set up a quantitative relationship between the consensus performance, measured by the ultimate consensus error bound, and the number of available bits per channel use.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Cao, Y., Yu, W., Ren, W., et al.: An overview of recent progress in the study of distributed multi-agent coordination. IEEE Trans. Ind. Inform. 9(1), 427–438 (2013)

    Article  Google Scholar 

  2. Alarcon Herrera, J.L., Chen, X.: Consensus algorithms in a multi-agent framework to Solve PTZ camera reconfiguration in UAVs. In: Su, C.-Y., Rakheja, S., Liu, H. (eds.) ICIRA 2012, Part I. LNCS, vol. 7506, pp. 331–340. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  3. Saber, R.O.: Flocking for multi-agent dynamic systems: algorithms and theory. IEEE Trans. Autom. Control 51(3), 401–420 (2006)

    Article  MathSciNet  Google Scholar 

  4. Lin, J., Morse, A.S., Anderson, B.D.O.: The multi-agent rendezvous problem - the asynchronous case. SIAM J. Control Optim. 46(6), 2120–2147 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  5. Fax, J.A., Murray, R.M.: Information flow and cooperative control of vehicle formations. IEEE Trans. Autom. Control 49(9), 1465–1476 (2004)

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  7. Saber, R.O., Fax, J.A., Murray, R.M.: Consensus and cooperation in networked multi-agent systems. Proc. IEEE 95(1), 215–233 (2007)

    Article  Google Scholar 

  8. Brockett, R.W., Liberzon, D.: Quantized feedback stabilization of linear systems. IEEE Trans. Autom. Control 4(7), 1279–1289 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  9. Elia, N., Mitter, S.K.: Stabilization of linear systems with limited information. IEEE Trans. Autom. Control 46(9), 1384–1400 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  10. Tatikonda, S., Mitter, S.: Control under communication constraints. IEEE Trans. Autom. Control 49(7), 1056–1068 (2004)

    Article  MathSciNet  Google Scholar 

  11. Kashyap, A., Basar, T., Srikant, R.: Quantized consensus. Automatica 43(7), 1192–1203 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  12. Cai, K., Ishii, H.: Gossip consensus and averaging algorithms with quantizaiton. In: Proceedings of American Control Conference, pp. 6306–6311 (2010)

    Google Scholar 

  13. Lavaei, J., Murray, R.M.: Quantized consensus by means of gossip algorithm. IEEE Trans. Autom. Control 57(1), 19–32 (2012)

    Article  MathSciNet  Google Scholar 

  14. Li, T., Fu, M., Xie, L., Zhang, J.: Distributed consensus with limited communication data rate. IEEE Trans. Autom. Control 56(2), 279–292 (2011)

    Article  MathSciNet  Google Scholar 

  15. Li, T., Xie, L.: Distributed coordination of multi-agent systems with quantized-observer based encoding-decoding. IEEE Trans. Autom. Control 57(12), 3023–3037 (2012)

    Article  MathSciNet  Google Scholar 

  16. Qiu, Z., Hong, Y., Xie, L.: Quantized leaderless and leader-following consensus of high-order multi-agent systems with limited data rate. In: IEEE Conference on Decision and Control, pp. 6759–6764 (2013)

    Google Scholar 

  17. You, K., Xie, L.: Network topology and communication data rate for consensusability of discrete-time multi-agent systems. IEEE Trans. Autom. Control 56(10), 2262–2275 (2011)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgement

This work was partially supported by the National Natural Science Foundation of China under Grant 61273112.

Author information

Authors and Affiliations

  1. Department of Automation, University of Science and Technology of China, Hefei, China

    Jiayu Chen & Qiang Ling

Authors
  1. Jiayu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qiang Ling
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qiang Ling .

Editor information

Editors and Affiliations

  1. Tokyo Metropolitan University , Tokyo, Japan

    Naoyuki Kubota

  2. Kyushu University , Fukuoka, Japan

    Kazuo Kiguchi

  3. University of Portsmouth , Portsmouth, United Kingdom

    Honghai Liu

  4. Tokyo Metropolitan University , Tokyo, Japan

    Takenori Obo

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Chen, J., Ling, Q. (2016). Quantized Consensus of Multi-agent Systems with Additive Noise. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9834. Springer, Cham. https://doi.org/10.1007/978-3-319-43506-0_43

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-43506-0_43

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43505-3

  • Online ISBN: 978-3-319-43506-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation