Journal of Intelligent & Robotic Systems

, Volume 74, Issue 1–2, pp 333–346 | Cite as

Cooperative Control of Multiple UAVs for Moving Source Seeking



Advances in multi-agent technologies and UAV technologies make it possible to take advantage of cooperation of multiple UAVs for source seeking. This paper focuses on moving source seeking using multiple UAVs with input constraints. Firstly, a least-squares method is introduced to estimate the gradient of the scalar field at the leader UAV location based on the measurements of all UAVs. Since the moving source velocity is unknown, an adaptive estimator is designed to obtain the velocity. Based on the estimated gradient and source velocity, a guidance law and a sliding mode based heading rate controller are proposed for the leader UAV to achieve level tracking. Heading rate controller for each follower UAV is also developed to achieve circular formation around the leader UAV. Furthermore, the gradient estimation error is analyzed and its influence on moving source velocity estimation and level tracking accuracy is explored as well. Finally, simulation results are provided to verify the proposed approach.


UAV Source seeking Formation control Adaptive estimation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Cochran, J., Krstic, M.: Nonholonomic source seeking with tuning of angular velocity. IEEE Trans. Autom. Control 54, 717–731 (2009)CrossRefMathSciNetGoogle Scholar
  2. 2.
    Zhang, C., Arnold, D., Ghods, N., Siranosian, A., Krstic, M.: Source seeking with nonholonomic unicycle without position measurement and with tuning of forward velocity. Syst. Control Lett. 56, 245–252 (2007)CrossRefMATHMathSciNetGoogle Scholar
  3. 3.
    Matveev, A.S., Teimoori, H., Savkin, A.V.: Navigation of a unicycle-like mobile robot for environmental extremum seeking. Automatica 47(1), 85–91 (2011)CrossRefMATHMathSciNetGoogle Scholar
  4. 4.
    Ogren, P., Fiorelli, E., Leonard, N.E.: Cooperative control of mobile sensor networks: adaptive gradient climbing in a distributed environment. IEEE Trans. Autom. Control 49(8), 1292–1302 (2004)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Han, J., Xu, Y., Di, L., Chen, Y.: Low-cost multi-UAV technologies for contour mapping of nuclear radiation field. J. Intell. Robot. Syst. 70(1–4), 401–410 (2013)CrossRefGoogle Scholar
  6. 6.
    Han, J., Chen, Y.: Cooperative source seeking and contour mapping of a diffusive signal field by formations of multiple UAVs. IEEE International Conference on Unmanned Aircraft Systems (ICUAS), pp. 35–40, Atlanta (2013)Google Scholar
  7. 7.
    Azuma, S., Sakar, M.S., Pappas, G.J.: Stochastic source seeking by mobile robots. IEEE Trans. Autom. Control 57(9), 2308–2321 (2012)CrossRefMathSciNetGoogle Scholar
  8. 8.
    Zhang, F., Leonard, N.E.: Cooperative filters and control for cooperative exploration. IEEE Trans. Autom. Control 55(3), 650–663 (2010)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Hu, J., Hu, X.: Nonlinear filtering in target tracking using cooperative mobile sensors. Automatica 46(12), 2041–2046 (2010)CrossRefMATHMathSciNetGoogle Scholar
  10. 10.
    Biyik, E., Arcak, M.: Gradient climbing in formation via extremum seeking and passivity-based coordination rules. In: 46th IEEE Conference on Decision and Control, pp. 3133–3138, New Orleans, LA (2007)Google Scholar
  11. 11.
    Ghods, N., Krstic, M.: Multiagent deployment over a source. IEEE Trans. Control Syst. Technol. 20(1), 277–285 (2012)Google Scholar
  12. 12.
    Li, S., Guo, Y.: Distributed source seeking by cooperative robots: all-to-all and limited communications. IEEE International Conference on Robotics and Automation, pp. 1107–1112. USA (2012)Google Scholar
  13. 13.
    Brinon-Arranz, L., Seuret, A., Canudas-de-Wit, C.: Collaborative estimation of gradient direction by a formation of AUVs under communication constraints. In: 50th IEEE Conference of Decision and Control and European Control Conference (CDC-ECC), pp. 5583–5588 (2011)Google Scholar
  14. 14.
    Moore, B.J., Canudas-de-Wit, C.: Source seeking via collaborative measurements by a circular formation of agents. In: American Control Conference (ACC), pp. 6417–6422 (2010)Google Scholar
  15. 15.
    Frew, E., Lawrence, D.: Cooperative standoff tracking of moving targets using Lyapunov guidance vector fields. AIAA J. Guid. Control. Dyn. 31(2), 290–306 (2008)CrossRefGoogle Scholar
  16. 16.
    Summers, T.H., Akella, M.R., Mears, M.J.: Coordinated standoff tracking of moving targets: control laws and information architectures. AIAA J. Guid. Control. Dyn. 32(1), 56–69 (2009)CrossRefGoogle Scholar
  17. 17.
    Zhu, S., Wang, D., Low, C.B.: Ground target tracking using UAV with input constraints. J. Intell. Robot. Syst. 69(1–4), 417–429 (2013)CrossRefGoogle Scholar
  18. 18.
    Zhu, S., Wang, D.: Adversarial ground target tracking using UAVs with input constraints. J. Intell. Robot. Syst. 65(1–4), 521–532 (2012)CrossRefMATHGoogle Scholar
  19. 19.
    Paley, D.A., Peterson, C.: Stabilization of collective motion in a time-invariant flowfield. AIAA J. Guid. Control. Dyn. 32(3), 771–779 (2009)CrossRefGoogle Scholar
  20. 20.
    Peterson, C., Paley, D.A.: Cooperative control of unmanned vehicle in a time-varying flowfield. In: Proceedings of AIAA Guidance, Navigation, and Control Conference (2009)Google Scholar
  21. 21.
    Peterson, C., Paley, D.A.: Multiple coordination in an estimated time-varying flowfield. AIAA J. Guid. Control. Dyn. 34(1), 177–191 (2011)CrossRefGoogle Scholar
  22. 22.
    Xu, B., Gao, D., Wang, S.: Adaptive neural control based on HGO for hypersonic flight vehicles. Sci. China Inf. Sci. 54(3), 511–520 (2011)CrossRefMATHMathSciNetGoogle Scholar
  23. 23.
    Xu, B., Sun, F., Yang, C., Gao, D., Ren, J.: Adaptive discrete-time controller design with neural network for hypersonic flight vehicle via back-stepping. Int. J. Control. 84(9), 1543–1552 (2011)CrossRefMATHMathSciNetGoogle Scholar
  24. 24.
    Xu, B., Sun, F., Liu, H., Ren, J.: Adaptive kriging controller design for hypersonic flight vehicle via back-stepping. IET Control Theory Appl. 6(4), 487–497 (2012)CrossRefMathSciNetGoogle Scholar
  25. 25.
    Zhu, S., Wang, D., Low, C.B.: Cooperative control of multiple UAVs for source seeking. J. Intell. Robot. Syst. 70(1–4), 293–301 (2013)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.EXQUISITUS, Centre for E-City, School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.DSO National Laboratories, INFO Division, Manned-Unmanned ProgrammeSingaporeSingapore

Personalised recommendations