Skip to main content
Log in

Containment Control of Multi-Agent Systems with Stochastic Multiplicative Noises

  • Published:
Journal of Systems Science and Complexity Aims and scope Submit manuscript

Abstract

This paper investigates the containment problem of continuous-time multi-agent systems with multiplicative noises, where the first-order and second-order multi-agent systems are studied respectively. Based on stochastic analysis tools, algebraic graph theory, and Lyapunov function method, the containment protocols based the relative states measurement with multiplicative noises are developed to guarantee the mean square and almost sure containment. Moreover, the sufficient conditions and necessary conditions related to the control gains are derived for achieving mean square and almost sure containment. It is also shown that multiplicative noises may works positively for the almost sure containment of the first-order multi-agent systems. Simulation examples are also introduced to illustrate the effectiveness of the theoretical results.

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.

Institutional subscriptions

Similar content being viewed by others

References

  1. Dimarogonas D V, Egerstedt M, and Kyriakopoulos K J, A leader-based containment control strategy for multiple unicycles, Proceedings of the 45th IEEE Conference on Decision and Control, San Diego, CA, USA, 2006.

  2. Cheah C C, Hou S P, and Slotine J J E, Region following formation control for multi-robot systems, 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, USA, 2008.

  3. Dong X W, Shi Z Y, Lu G, et al., Output containment analysis and design for high-order linear time-invariant swarm systems, International Journal of Robust and Nonlinear Control, 2015, 25(6): 900–913.

    Article  MathSciNet  Google Scholar 

  4. Cheng L, Wang Y, Ren W, et al., Containment control of multi-agent systems with dynamic leaders based on a PIn-type approach, IEEE Transactions on Cybernetics, 2016, 46(12): 3004–3017.

    Article  Google Scholar 

  5. Meng Z Y, Ren W, and Zheng Y, Distributed finite-time attitude containment control for multiple rigid bodies, Automatica, 2010, 46(12): 2092–2099.

    Article  MathSciNet  Google Scholar 

  6. Belta C and Kumar V, Trajectory design for formations of robots by kinetic energy shaping, IEEE International Conference on Robotics and Automation, Washington, DC, 2002.

  7. Ji M, Ferrari-Trecate G, Egerstedt M, et al., Containment control in mobile networks, IEEE Transactions on Automatic Control, 2008, 53(8): 1972–1975.

    Article  MathSciNet  Google Scholar 

  8. Cao Y C, Ren W, and Egerstedt M, Distributed containment control with multi-ple stationary or dynamic leaders in fixed and switching directed networks, Automatica, 2012, 48(8): 1586–1597.

    Article  MathSciNet  Google Scholar 

  9. Notarstefano G, Egerstedt M, and Haque M, Containment in leader-follower networks with switching communication topologies, Automatica, 2011, 47(5): 1035–1040.

    Article  MathSciNet  Google Scholar 

  10. Ajorlou A, Momeni A, and Aghdam A G, A class of bounded distributed control strategies for connectivity preservation in multi-agent systems, IEEE Transactions on Automatic Control, 2010, 55(12): 2828–2833.

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  12. Cao Y C, Stuart D, Ren W, et al., Distributed containment control for multiple autonomous vehicles with double-integrator dynamics: Algorithms and experiments?, IEEE Transactions on Control Systems Technology, 2011, 19(4): 929–938.

    Article  Google Scholar 

  13. Li J Z, Ren W, and Xu S Y, Distributed containment control with multiple dynamic leaders for double-integrator dynamics using only position measurements, IEEE Transactions on Automatic Control, 2012, 57(6): 1553–1559.

    Article  MathSciNet  Google Scholar 

  14. Chen F, Ren W, and Lin Z L, Multi-leader multi-follower coordination with cohesion, dispersion, and containment control via proximity graphs, Science in China Series F: Information Sciences, 2017, 60(11): 105–124.

    MathSciNet  Google Scholar 

  15. Zhu W and Cheng D, Leader-following consensus of second-order agents with multiple time-varying delays, Automatica, 2010, 46(12): 1994–1999.

    Article  MathSciNet  Google Scholar 

  16. Yu W W, Chen G R, and Cao M, Distributed leader-follower flocking control for multi-agent dynamical systems with time-varying velocities, Systems & Control Letters, 2010, 59(9): 543–552.

    Article  MathSciNet  Google Scholar 

  17. Sun F L, Chen J C, Guan Z H, et al., Leader-following finite-time consensus for multi-agent systems with jointly-reachable leader?, Nonlinear Analysis: Real World Applications, 2012, 13(5): 2271–2284.

    Article  MathSciNet  Google Scholar 

  18. Liu J W and Huang J, Leader-following consensus of linear discrete-time multi-agent systems subject to jointly connected switching networks, Science China (Information Sciences), 2018, 61(11): 171–178.

    MathSciNet  Google Scholar 

  19. Ni Y H and Li X, Consensus seeking in multi-agent systems with multiplicative measurement noises, Systems & Control Letters, 2013, 62(5): 430–437.

    Article  MathSciNet  Google Scholar 

  20. Djaidja S and Wu Q H, Leader-following consensus for single-integrator multi-agent systems with multiplicative noises in directed topologies, International Journal of Systems Science, 2015, 46(15): 2788–2798.

    Article  MathSciNet  Google Scholar 

  21. Zong X F, Li T, Yin G, et al., Stochastic consentability of linear systems with time delays and multiplicative noises, IEEE Transactions on Automatic Control, 2018, 63(4): 1059–1074.

    Article  MathSciNet  Google Scholar 

  22. Zong X F, Li T, and Zhang J F, Consensus conditions for continuous-time multi-agent systems with time-delays and measurement noises, Automatica, 2019, 99(99): 412–419.

    Article  MathSciNet  Google Scholar 

  23. Wang Y P, Cheng L, Hou Z G, et al., Containment control of multi-agent systems in a noisy communication environment, Automatica, 2014, 50(7): 1922–1928.

    Article  MathSciNet  Google Scholar 

  24. Du Y X, Wang Y J, and Zuo Z Q, Containment control of multi-agent systems with measured noise based on the Kalman-Bucy filtering theory, 36th Chinese Control Conference (CCC), 2017.

  25. Du Y X, Wang Y J, Zuo Z Q, et al., Containment control for distributed networks subject to multiplicative and additive noises with stochastic approximation-type protocols, International Journal of Robust and Nonlinear Control, 2020, 30(2): 665–684.

    Article  MathSciNet  Google Scholar 

  26. Li W Q, Liu L, and Feng G, Distributed containment tracking of multiple stochastic nonlinear systems, Automatica, 2016, 69(69): 214–221.

    Article  MathSciNet  Google Scholar 

  27. Li T, Wu F, and Zhang J F, Multi-agent consensus with relative-state-dependent measurement noises, IEEE Transactions on Automatic Control, 2014, 59(9): 2463–2468.

    Article  MathSciNet  Google Scholar 

  28. Zhang Y Y, Li R F, Zhao W, et al., Stochastic leader-following consensus of multi-agent systems with measurement noises and communication time-delays, Neurocomputing, 2018, 282(22): 136–145.

    Article  Google Scholar 

  29. Xiao F and Wang L, Consensus behavior of agents in networked systems under general communication topologies, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, Munich, 2006.

  30. Wei H, Lü Q, Duo N, et al., Consensus algorithms based multi-robot formation control under noise and time delay conditions, Applied Sciences, 2019, 9(5): 1004–1019.

    Article  Google Scholar 

  31. Zhang Q and Zhang J F, Quantized data-based distributed consensus under directed time-varying communication topology, SIAM Journal on Control and Optimization, 2013, 51(1): 332–352.

    Article  MathSciNet  Google Scholar 

  32. Mao X R, Stochastic Differential Equations and Applications, Horwood Publications, Chichester, 1998.

    Google Scholar 

  33. Khasminskii R, Stochastic Stability of Differential Equations, Springer, New York, 1980.

    Book  Google Scholar 

  34. Cao Y C, Stuart D, Ren W, et al., Distributed containment control for multiple autonomous vehicles with double-integrator dynamics: Algorithms and experiments, IEEE Transactions on Control Systems Technology, 2011, 19(4): 929–938.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaofeng Zong.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 61703378, 62073305 and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan).

This paper was recommended for publication by Editor CAO Ming.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ren, J., Zong, X. Containment Control of Multi-Agent Systems with Stochastic Multiplicative Noises. J Syst Sci Complex 35, 909–930 (2022). https://doi.org/10.1007/s11424-021-0167-4

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11424-021-0167-4

Keywords

Navigation