Skip to main content
Log in

Containment Control of Multi-agent Systems with Uniform Quantization

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

In this paper, the problem of containment control is investigated for a class of multi-agent systems with second-order integrator dynamics. A directed graph is considered, and a pair of matrix norm and vector norm is designed. Accounting for the limitation of the finite bandwidth channels, quantized communication topology based on the encoding–decoding strategy is designed, in which the quantizers only have finite quantization levels and it is independent of the initial state of agents. Moreover, the quantizer and controller are jointly designed only using the estimated value of the neighbors’ state information to ensure the system stability with less communication resource. The relationship between the quantization levels and sampling interval is established to guarantee that all the quantizers are not saturated, and thus ensure the asymptotic stability of the system. And a vector norm induced by a constructed matrix norm is applied to reduce the lower boundary of the communication data rate which is free from the dimension and number of agents. Finally, simulation examples are given to show the effectiveness of the new designed techniques.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. C.V. Analikwu, H.M. Schwartz, Multi-agent learning in the game of guarding a territory. Int. J. Innov. Comput. Inf. Control 13(6), 1855–1872 (2017)

    Google Scholar 

  2. G.C. Campos, J.M.G. da Silva, S. Tarbouriech, C.E. Pereira, Stabilisation of discrete-time systems with finite-level uniform and logarithmic quantisers. IET Control Theory Appl. 12(8), 1125–1132 (2018)

    Article  MathSciNet  Google Scholar 

  3. L. Chen, M. Liu, X. Huang, S. Fu, J. Qiu, Adaptive fuzzy sliding mode control for network-based nonlinear systems with actuator failures. IEEE Trans. Fuzzy Syst. 26(3), 1311–1323 (2018)

    Article  Google Scholar 

  4. X. Chen, X.F. Liao, L. Gao, S. Yang, H. Wang, H. Li, Event-triggered consensus for multi-agent networks with switching topology under quantized communication. Neurocomputing 230, 294–301 (2017)

    Article  Google Scholar 

  5. M. Enayat, K. Khorasani, Semi-decentralized nonlinear cooperative control strategies for a network of heterogeneous autonomous underwater vehicles. Int. J. Robust Nonlinear Control 27(16), 2688–2707 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  6. R.A. Horn, C.R. Johnson, Matrix Analysis (Cambridge University, Cambridge, 1986)

    Google Scholar 

  7. W. Hu, L. Liu, G. Feng, Cooperative output regulation of linear multi-agent systems by intermittent communication: a unified framework of time- and event-triggering strategies. IEEE Trans. Autom. Control 63(2), 548–555 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  8. M.A. Kamel, X. Yu, Y. Zhang, Fault-tolerant cooperative control design of multiple wheeled mobile robots. IEEE Trans. Control Syst. Technol. 26(2), 756–764 (2018)

    Article  Google Scholar 

  9. B. Li, Z. Chen, C. Zhang, Z. Liu, Q. Zhang, Containment control for directed networks multi-agent system with nonlinear dynamics and communication time-delays. Int. J. Control Autom. Syst. 15(3), 1181–1188 (2017)

    Article  Google Scholar 

  10. J. Li, Z. Guan, R. Liao, D. Zhang, Impulsive containment control for second-order networked multi-agent systems with sampled information. Nonlinear Anal. Hybrid Syst. 12, 93–103 (2014)

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  12. Z. Li, W. Ren, X. Liu, M. Fu, Distributed containment control of multi-agent systems with general linear dynamics in the presence of multiple leaders. Int. J. Robust Nonlinear Control 23(5), 534–547 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  13. H. Liu, G. Xie, L. Wang, Necessary and sufficient conditions for containment control of networked multi-agent systems. Automatica 48(7), 1415–1422 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  14. Z. Meng, W. Ren, Z. You, Distributed finite-time attitude containment control for multiple rigid bodies. Automatica 46(12), 2092–2099 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  15. X. Mu, K. Liu, Containment control of single-integrator network with limited communication data rate. IEEE Trans. Autom. Control 61(8), 2232–2238 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  16. K.K. Oh, M.C. Park, H.S. Ahn, A survey of multi-agent formation control. Automatica 53, 424–440 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  17. Z. Qiu, L. Xie, Y. Hong, Quantized leaderless and leader-following consensus of high-order multi-agent systems with limited data rate. IEEE Trans. Autom. Control 61(9), 2432–2447 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  18. R. Sakthivel, S. Santra, K. Mathiyalagan, H. Su, Robust reliable control design for networked control system with sampling communication. Int. J. Control 88(12), 2510–2522 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  19. S. Santra, R. Sakthivel, Y. Shi, K. Mathiyalagan, Dissipative sampled-data controller design for singular networked cascade control systems. J. Frankl. Inst. Eng. Appl. Math. 353(14), 3386–3406 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  20. Q. Shen, P. Shi, Distributed command filtered backstepping consensus tracking control of nonlinear multiple-agent systems in strict-feedback form. Automatica 53, 120–124 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  21. P. Shi, Q. Shen, Cooperative control of multi-agent systems with unknown state-dependent controlling effects. IEEE Trans. Autom. Sci. Eng. 12(3), 827–834 (2015)

    Article  Google Scholar 

  22. P. Shi, Q. Shen, Observer-based leader-following consensus of uncertain nonlinear multi-agent systems. Int. J. Robust Nonlinear Control 27(17), 3794–3811 (2017)

    MathSciNet  MATH  Google Scholar 

  23. E. Simetti, G. Casalino, Manipulation and transportation with cooperative underwater vehicle manipulator systems. IEEE J. Ocean. Eng. 42(4), 782–799 (2017)

    Article  Google Scholar 

  24. R. Sombutkaew, O. Chitsobhuk, D. Prapruttam, T. Ruangchaijatuporn, Adaptive quantization via fuzzy classified priority mapping for liver ultrasound compression. Int. J. Innov. Comput. Inf. Control 12(2), 635–649 (2016)

    Google Scholar 

  25. H. Su, M.Z.Q. Chen, Multi-agent containment control with input saturation on switching topologies. IET Control Theory Appl. 9(3), 399–409 (2015)

    Article  MathSciNet  Google Scholar 

  26. Q. Tang, H. Zhou, Z. Liu, W. Hu, W. Wang, Distributed consensus tracking with stochastic quantization via pulse-modulated intermittent control. J. Frankl. Inst. Eng. Appl. Math. 354(8), 3485–3501 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  27. X. Wang, S. Li, X. Yu, J. Yang, Distributed active anti-disturbance consensus for leader-follower higher-order multi-agent systems with mismatched disturbances. IEEE Trans. Autom. Control 62(11), 5795–5801 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  28. S. Weng, D. Yue, Distributed event-triggered cooperative attitude control of multiple rigid bodies with leader–follower architecture. Int. J. Syst. Sci. 47(3), 631–643 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  29. X. Yu, L. Liu, Cooperative control for moving-target circular formation of nonholonomic vehicles. IEEE Trans. Autom. Control 62(7), 3448–3454 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  30. X. Zhang, X. Liu, Consensus tracking of second order multi-agent systems with disturbances under heterogenous position and velocity topologies. Int. J. Control Autom. Syst. 16(5), 2334–2342 (2018)

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially supported by the National Nature Science Foundation of China (61773131, U1509217) and the Australian Research Council (DP170102644).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peng Shi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, L., Shi, P., Zhao, Y. et al. Containment Control of Multi-agent Systems with Uniform Quantization. Circuits Syst Signal Process 38, 3952–3970 (2019). https://doi.org/10.1007/s00034-019-01042-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-019-01042-z

Keywords

Navigation