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Control Theory and Technology

, Volume 16, Issue 2, pp 82–92 | Cite as

Flocking control of a fleet of unmanned aerial vehicles

  • Adel Belkadi
  • Zhixiang Liu
  • Laurent Ciarletta
  • Youmin Zhang
  • Didier Theilliol
Article
  • 71 Downloads

Abstract

Current applications using single unmanned vehicle have been gradually extended to multiple ones due to their increased efficiency in mission accomplishment, expanded coverage areas and ranges, as well as enhanced system reliability. This paper presents a flocking control method with application to a fleet of unmanned quadrotor helicopters (UQHs). Three critical characteristics of formation keeping, collision avoidance, and velocity matching have been taken into account in the algorithm development to make it capable of accomplishing the desired objectives (like forest/pipeline surveillance) by safely and efficiently operating a group of UQHs. To achieve these, three layered system design philosophy is considered in this study. The first layer is the flocking controller which is designed based on the kinematics of UQH. The modified Cucker and Smale model is used for guaranteeing the convergence of UQHs to flocking, while a repelling force between each two UQHs is also added for ensuring a specified safety distance. The second layer is the motion controller which is devised based on the kinetics of UQH by employing the augmented state-feedback control approach to greatly minimize the steady-state error. The last layer is the UQH system along with its actuators. Two primary contributions have been made in this work: first, different from most of the existing works conducted on agents with double integrator dynamics, a new flocking control algorithm has been designed and implemented on a group of UQHs with nonlinear dynamics. Furthermore, the constraint of fixed neighbouring distance in formation has been relaxed expecting to significantly reduce the complexity caused by the increase of agents number and provide more flexibility to the formation control. Extensive numerical simulations on a group of UQH nonlinear models have been carried out to verify the effectiveness of the proposed method.

Keywords

Flocking unmanned aerial vehicles unmanned quadrotor helicopters Cucker and Smale formation control 

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References

  1. [1]
    C. Yuan, Y. Zhang, Z. Liu. A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques. Canadian Journal of Forest Research, 2015, 45(7): 783–792.CrossRefGoogle Scholar
  2. [2]
    C. Yuan, Z. Liu, Y. Zhang. Aerial images-based forest fire detection for firefighting using optical remote sensing techniques and unmanned aerial vehicles. Journal of Intelligent & Robotic Systems, 2017, 88(2/4): 635–654.CrossRefGoogle Scholar
  3. [3]
    D. Kingston, R. W. Beard, R. S. Holt. Decentralized perimeter surveillance using a team of UAVs. IEEE Transactions on Robotics, 2008, 24(6): 1394–1404.CrossRefGoogle Scholar
  4. [4]
    A. Rango, A. Laliberte, J. E. Herrick, et al. Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management. Journal of Applied Remote Sensing, 2009, 3(1): DOI 10.1117/1.3216822.Google Scholar
  5. [5]
    J. E. Gomez-Balderas, G. Flores, L. G. Carrillo, et al. Tracking a ground moving target with a quadrotor using switching control. Journal of Intelligent & Robotic Systems, 2013, 70(1/4): 65–78.CrossRefGoogle Scholar
  6. [6]
    J. Escareno, S. Salazar, H. Romero, et al. Trajectory control of a quadrotor subject to 2D wind disturbances. Journal of Intelligent & Robotic Systems, 2013, 70(1/4): 51–63.CrossRefGoogle Scholar
  7. [7]
    Z. Liu, C. Yuan, X. Yu, et al. Retrofit fault-tolerant tracking control design of an unmanned quadrotor helicopter considering actuator dynamics. International Journal of Robust and Nonlinear Control, 2017: DOI https://doi.org/10.1002/rnc.3889. Google Scholar
  8. [8]
    Z. Liu, C. Yuan, Y. Zhang, et al. A learning-based fault tolerant tracking control of an unmanned quadrotor helicopter. Journal of Intelligent & Robotic Systems, 2015, 84(1/4): 145–162.Google Scholar
  9. [9]
    C. W. Reynolds. Flocks, herds and schools: A distributed behavioral model. ACM SIGGRAPH Computer Graphics, 1987, 21(4): 25–34.CrossRefGoogle Scholar
  10. [10]
    R. Olfati-Saber. Flocking for multi-agent dynamic systems: Algorithms and theory. IEEE Transactions on Automatic Control, 2006, 51(3): 401–420.MathSciNetCrossRefzbMATHGoogle Scholar
  11. [11]
    F. Cucker, S. Smale. On the mathematics of emergence. Japanese Journal of Mathematics, 2007, 2(1): 197–227.MathSciNetCrossRefzbMATHGoogle Scholar
  12. [12]
    T. Vicsek, A. Czirók, E. Ben-Jacob, et al. Novel type of phase transition in a system of self-driven particles. Physical Review Letters, 1995, 75(6): 1226–1229.MathSciNetCrossRefGoogle Scholar
  13. [13]
    Z. Liu, L. Guo. Connectivity and synchronization of Vicsek model. Science in China Series F: Information Sciences, 2008, 51(7): 848–858.MathSciNetCrossRefzbMATHGoogle Scholar
  14. [14]
    L. Perea, E. Pedro, G. Gerard. Extension of the Cucker-Smale control law to space flight formations. Journal of Guidance, Control, and Dynamics, 2009, 32(2): 527–537.CrossRefGoogle Scholar
  15. [15]
    F. Cucker, J. G. Dong. Avoiding collisions in flocks. IEEE Transactions on Automatic Control, 2010, 55(5): 1238–1243.MathSciNetCrossRefzbMATHGoogle Scholar
  16. [16]
    J. Park, H. J. Kim, S. Y. Ha. Cucker-Smale flocking with interparticle bonding forces. IEEE Transactions on Automatic Control, 2010, 55(11): 2617–2623.MathSciNetCrossRefzbMATHGoogle Scholar
  17. [17]
    S. M. Ahn, H. Choi, S. Y. Ha, et al. On collision-avoiding initial configurations to Cucker-Smale type flocking models. Communications in Mathematical Sciences, 2012, 10(2): 625–643.MathSciNetCrossRefzbMATHGoogle Scholar
  18. [18]
    R. Olfati-Saber, R. M. Murray. Consensus problems in networks of agents with switching topology and time-delays. IEEE Transactions on Automatic Control, 2004, 49(9): 1520–1533.MathSciNetCrossRefzbMATHGoogle Scholar
  19. [19]
    N. Moshtagh, N. Michael, A. Jadbabaie, et al. Visionbased, distributed control laws for motion coordination of nonholonomic robots. IEEE Transactions on Robotics, 2009, 25(4): 851–860.CrossRefGoogle Scholar
  20. [20]
    O. Saif, F. Isabelle, Z. R. Arturo. Real-time flocking of multiplequadrotor system of systems. IEEE Conference on System of Systems Engineering (SoSE), San Antonio: IEEE, 2015: 286–291.Google Scholar
  21. [21]
    A. Belkadi, D. Theilliol, L. Ciarletta, et al. Robust flocking control design for a fleet of autonomous agents. IEEE Conference on Control and Fault-Tolerant Systems (SysTol), Barcelona: IEEE, 2016: 1–6.Google Scholar
  22. [22]
    Z. Liu, C. Yuan, Y. Zhang. Active fault-tolerant control of unmanned quadrotor helicopter using linear parameter varying technique. Journal of Intelligent & Robotic Systems, 2017, 88(2/4): 415–436.CrossRefGoogle Scholar
  23. [23]
    Y. Zhang, A. Chamseddine, C. A. Rabbath, et al. Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed. Journal of Franklin Institute, 2013, 350(9): 2396–2422.CrossRefzbMATHGoogle Scholar
  24. [24]
    Z. Liu, Y. Zhang, X. Yu, et al. Unmanned surface vehicles: An overview of developments and challenges. Annual Reviews in Control, 2016, 41: 71–93.CrossRefGoogle Scholar
  25. [25]
    K. J. Åström, B. Wittenmark. Computer-Controlled Systems: Theory and Design. Englewood Cliffs: Prentice-Hall, 1984.Google Scholar
  26. [26]
    Y. Zhang, J. Jiang. Integrated design of reconfigurable faulttolerant control systems. Journal of Guidance, Control, and Dynamics, 2001, 24(1): 133–136.CrossRefGoogle Scholar
  27. [27]
    B. Kedjar, A. H. Kamal. DSP-based implementation of an LQR with integral action for a three-phase three-wire shunt active power filter. IEEE Transactions on Industrial Electronics, 2009, 56(8): 2821–2828.CrossRefGoogle Scholar

Copyright information

© South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Adel Belkadi
    • 1
  • Zhixiang Liu
    • 2
  • Laurent Ciarletta
    • 3
  • Youmin Zhang
    • 2
  • Didier Theilliol
    • 1
  1. 1.CRAN, University of LorraineNancyFrance
  2. 2.Department of Mechanical, Industrial and Aerospace EngineeringConcordia UniversityMontrealCanada
  3. 3.Lorraine Research Laboratory in Computer Science and its Applications (LORIA)University of LorraineNancyFrance

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