Skip to main content
SpringerLink
Log in

Distributed control and speed sensorless for the synchronisation of multi-robot systems

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

This paper investigates a synchronization approach to trajectory tracking of networked robotic systems while maintaining time-varying formations. The objective is to control networked robots to track a desired trajectory while synchronizing their behaviors. Combining trajectory tracking and synchronization algorithms, the developed approach uses a cross-coupling technical to create interconnections for mutual synchronization of robots. The main objective of distributed approach is to generate an emerging behavior using only local information interactions. First, a distributed scheme is developed to achieve the networked robots synchronization on undirected graph. Then, the leaderless synchronized tracking problem in the case when only position measurements are available, will be presented. For both cases: In the presence of the velocity feedback or in its absence, the controller, designed by incorporating the cross-coupling technical into a sliding mode control architecture, successfully guarantees asymptotic convergence to zero of both position tracking and synchronization errors simultaneously. The Lyapunov-based approach has been used to establish the multi-robot systems asymptotic stability. A real-time software simulator is developed to visualize the synchronized behaviors. Based on LabVIEW integrated development environment (IDE), a developed human-machine-interface (HMI) allows its user to control, in real time, the networked robots. Simulation and experimental results are provided to demonstrate performances of the proposed control schemes.

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

Access this article

Log in via an institution

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. Davidson, A.J. and Menake, M., Birds of a feather clock together sometimes: Social synchronization of circadian rhythms, Curr. Opin. Neurobiol., 2003, vol. 13, no. 6, pp. 765–769.

    Article  Google Scholar 

  2. Bjrnsson, B. and Reynisson, P., Synchronous and vertically undulating swimming behaviour of Atlantic cod Gadus morhua, Aquat. Biol., 2013, vol. 19, pp. 13–18.

    Article  Google Scholar 

  3. Fan, X.M., Zhang, Sh.J., Hapeshi, K., and Yang, Y.Sh., Biological system behaviours and natural-inspired methods and their applications to supply chain management, Appl. Mech. Mater., 2013, vol. 461, pp. 942–958.

    Article  Google Scholar 

  4. Bouteraa, Y., Ghommam, J., Derbel, N., and Poisson, G., Non-linear adaptive synchronisation control of multi-agent robotic systems, Int. J. Syst. Control Commun., 2012, vol. 4, nos. 1–2.

    Google Scholar 

  5. Rezaee, H. and Farzaneh, A., Motion synchronization in unmanned aircrafts formation control with communication delays, Commun. Nonlinear Sci. Num. Simul., 2013, vol. 18, no. 3, pp. 744–756.

    Article  MathSciNet  MATH  Google Scholar 

  6. Acevedo, J.J., Arrue, B.C., Diaz-Banez, J.M., Ventura, I., Maza, I., and Ollero, A., One-to-one coordination algorithm for decentralized area partition in surveillance missions with a team of aerial robots, J. Intell. Rob. Syst., 2014, vol. 74, nos. 1–2, pp. 269–285.

    Article  Google Scholar 

  7. Bouteraa, Y., Ghommam, J., Derbel, N., and Poisson, G., “Nonlinear control and synchronization with time delays of multi-agent robotic systems”, J. Control Sci. Eng., 2011.

    Google Scholar 

  8. Tuna, G., Nefzi, B. and Conte, G., Unmanned aerial vehicle-aided communications system for disaster recovery, J. Network Comput. Appl., 2014, vol. 41, pp. 27–36.

    Article  Google Scholar 

  9. Mei, J., Ren, W., and Ma, G., Distributed coordinated tracking with a dynamic leader for multiple Euler–Lagrange systems, IEEE Trans. Autom. Control, 2011, vol. 56, no. 6, pp. 1415–1421.

    Article  MathSciNet  Google Scholar 

  10. Wei Ren, Distributed cooperative attitude synchronization and tracking for multiple rigid bodies, IEEE Trans. Control Syst. Technol., 2010, vol. 18, no. 2, pp. 383–392.

    Article  Google Scholar 

  11. Hyo-Sung Ahn, Moore, K.L., and Yang Quan Chen, Trajectory-keeping in satellite formation flying via robust periodic learning control, Int. J. Robust Nonlinear Control, 2010.

    Google Scholar 

  12. Das, A. and Lewis, F.L., Distributed adaptive control for synchronization of unknown nonlinear networked systems, Automatica, 2010, vol. 46, no. 12, pp. 2014–2021.

    Article  MathSciNet  MATH  Google Scholar 

  13. Cao, Y. and Ren, W., Distributed coordinated tracking with reduced interaction via a variable structure approach, IEEE Trans. Autom. Control, 2012, vol. 57, no. 1, pp. 33–48.

    Article  MathSciNet  Google Scholar 

  14. Hong, Y., Chen, G., and Bushnell, L., Distributed observers design for leader following control of multi-agent networks, Automatica, 2008, vol. 44, no. 3, pp. 846–850.

    Article  MathSciNet  MATH  Google Scholar 

  15. Olfati-Saber, R., Flocking for multi-agent dynamic systems: Algorithms and theory, IEEE Trans. Autom. Control, 2006, vol. 51, no. 3, pp. 401–420.

    Article  MathSciNet  Google Scholar 

  16. Qin, J., Zheng, W., and Gao, H., Consensus of multiple second-order vehicles with a time-varying reference signal under directed topology, Automatica, 2011, vol. 47, no. 6, pp. 1983–1991.

    Article  MathSciNet  MATH  Google Scholar 

  17. Su, H., Chen, G., Wang, X., and Lin, Z., Adaptive second-order consensus of networked mobile agents with nonlinear dynamics, Automatica, 2011, vol. 46, no. 2, pp. 368–375.

    Article  MathSciNet  MATH  Google Scholar 

  18. Olfati-Saber, R., Flocking for multi-agent dynamic systems: Algorithms and theory, IEEE Trans. Autom. Control, 2006, vol. 51, no. 3, pp. 401–420.

    Article  MathSciNet  Google Scholar 

  19. Fax, J.A. and Murray, R.M., Information flow and cooperative control of vehicle formations, IEEE Trans. Autom. Control, 2004, vol. 49, no. 9, pp. 1465–1476.

    Article  MathSciNet  Google Scholar 

  20. Tanner, H.G., Jadbabaie, A., and Pappas, G.J., Flocking in fixed and switching networks, IEEE Trans. Autom. Control, 2007, vol. 52, no. 5, pp. 863–868.

    Article  MathSciNet  Google Scholar 

  21. Dimarogonas, D.V. and Kyriakopoulos, K.J., Connectedness preserving distributed swarm aggregation for multiple kinematic robots, IEEE Trans. Robot., 2008, vol. 24, no. 5, pp. 1213–1223.

    Article  Google Scholar 

  22. Olfati-Saber, R., Flocking for multi-agent dynamic systems: Algorithms and theory, IEEE Trans. Autom. Control, 2006, vol. 51, no. 3, pp. 401–420.

    Article  MathSciNet  Google Scholar 

  23. Su, H., Wang, X., and Lin, Z., Flocking of multi-agents with a virtual leader, IEEE Trans. Autom. Control, 2009, vol. 54, no. 2, pp. 293–307.

    Article  MathSciNet  Google Scholar 

  24. Li, J., Ren, W., and Xu, S., Distributed containment control with multiple dynamic leaders for double-integrator dynamics using only position measurements, IEEE Trans. Autom. Control, 2012, no. 6, vol. 57, no. 6, pp. 1553–1559.

    Article  MathSciNet  Google Scholar 

  25. Laidi, L., Benmansour, K., Ferdjouni, A., and Bouchhida, Q., Real-time implementation of an interconnected observer design for p-cells chopper, Archives Electr. Eng., 2010, vol. 59, nos. 1–2. doi doi 10.2478/s10171-010-0001-4

    Google Scholar 

  26. Lin, Z., Broucke, M., and Francis, B., Local control strategies for groups of mobile autonomous agents, IEEE Trans. Autom. Control, 2004, vol. 49, no. 4, pp. 622–629.

    Article  MathSciNet  Google Scholar 

  27. Ren, W., Multi-vehicle consensus with a time-varying reference state, Syst. Control Lett., vol. 56, nos. 7–8, pp. 474–483.

  28. Ren, W., Beard, R.W., and Atkins, E., Information consensus in multivehicle cooperative control: Collective group behavior through local interaction, IEEE Control Syst. Mag., 2007, vol. 27, no. 2, pp. 71–82.

    Article  Google Scholar 

  29. Hong, Y., Hu, J., and Gao, L., Tracking control for multi-agent consensus with an active leader and variable topology, Automatica, 2007, vol. 42, no. 7, pp. 1177–1182.

    Article  MathSciNet  MATH  Google Scholar 

  30. Hong, Y., Chen, G., and Bushnell, L., Distributed observers design for leader following control of multi-agent networks, Automatica, 2008, vol. 44, no. 3, pp. 846–850.

    Article  MathSciNet  MATH  Google Scholar 

  31. Mien Van, Hee-Jun Kang, and Young-Soo Suh, Second order sliding mode-based output feedback tracking control for uncertain robot manipulators, Int. J. Adv. Rob. Syst., 2012.

    Google Scholar 

  32. Gao, Y., Wang, L., and Jia, Y., Consensus of multiple second-order agents without velocity measurements, Proceedings of the American Control Conference, St. Louis, MO, 2009.

    Google Scholar 

  33. Abdessameud, A. and Tayebi, A., On consensus algorithms for double integrator dynamics without velocity measurements and with input constraints, Syst. Control Lett., 2010, vol. 59, no. 12, pp. 812–822.

    Article  MathSciNet  MATH  Google Scholar 

  34. Rodriguez-Angeles, A. and Nijmeijer, H., Mutual synchronization of robots via estimated: State feedback: A cooperative approach, IEEE Trans. Control Syst. Technol., 2004, vol. 12, no. 4.

    Google Scholar 

  35. Dong Sun, Can Wang, Wen Shang, and Gang Feng, A synchronization approach to trajectory tracking of multiple mobile robots while maintaining time-varying formations, IEEE Trans. Rob., 2009, vol. 25, no. 5.

    Google Scholar 

  36. Abdessameud, A. and Tayebi, A., Global trajectory tracking control of VTOL-UAVs without linear velocity measurements, Automatica, 2010, vol. 46, pp. 1053–1059.

    Article  MathSciNet  MATH  Google Scholar 

  37. Kyrkjeb, E. and Pettersen, K.Y., Operational space synchronization of two robot manipulators through a virtual velocity estimate, Model., Identif., Control, 2008, vol. 29, no. 2, pp. 59–66.

    Article  Google Scholar 

  38. Xinhua Wang, Jinkun Liu, and Kai-Yuan Cai, Tracking control for a velocity-sensorless VTOL aircraft with delayed outputs, Automatica, 2009, vol. 45, no. 12, pp. 2876–2882.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Digital Research Center of Sfax, Control and Energy Management Laboratory (CEM-Lab) National School of Engineers of Sfax, Sfax, Tunisia

    Yassine Bouteraa & Ismail Ben Abdallah

Authors
  1. Yassine Bouteraa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ismail Ben Abdallah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yassine Bouteraa.

Additional information

The article is published in the original.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bouteraa, Y., Abdallah, I.B. Distributed control and speed sensorless for the synchronisation of multi-robot systems. Aut. Control Comp. Sci. 50, 306–317 (2016). https://doi.org/10.3103/S0146411616050023

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411616050023

Keywords

Search

Navigation