Automatic tuning of a behavior-based guidance algorithm for formation flight of quadrotors

Document Type : Original Article


The University of Tehran


This paper presents a tuned behavior-based guidance algorithm for formation flight of quadrotors. The behavior-based approach provides the basis for the simultaneous realization of different behaviors such as leader following and obstacle avoidance for a group of agents; in our case they are quadcopters. In this paper optimization techniques are utilized to tune the parameters of a behavior-based guidance algorithm; to compromise between safety, trajectory optimality, and control effort during the formation flight. The tuning is formulated as a constraint optimization problem where the penalty function method is used to secure the safe passage of quadrotors around an obstacle. The guidance subsystem is integrated with a consistent dynamic inversion controller to realize a smooth maneuver of the quadrotors along desired trajectories. For more, MATLAB/Simulink is used as the programming platform. The effectiveness of the tuning method is verified, based on the performance of the closed-loop system in the presence of an overall navigation system uncertainties and actuator lags.


Main Subjects

Article Title [فارسی]

تنظیم خودکار هدایت رفتار محور برای پرواز گروهی پرنده چهار-پره

Authors [فارسی]

  • احسان زیبایی
  • محمد علی امیری آتشگاه
[1]   R. J. Ray, B. R. Cobleigh, M. J. Vachon, and C. StJohn, “Flight test techniques used to evaluate performance benefits during formation flight,” in NASA Conference publication, 2002.
[2]   Z. A. Bangash, R. P. Sanchez, A. Ahmed, and M. J. Khan, “Aerodynamics of formation flight,” J. Aircr., vol. 43, no. 4, pp. 907–912, 2006.
[3]   D. P. Scharf, F. Y. Hadaegh, and S. R. Ploen, “A survey of spacecraft formation flying guidance and control (part I): Guidance,” in Proceedings of the American control conference, 2003, vol. 2, pp. 1733–1739.
[4]   M. S. Alvissalim et al., “Swarm quadrotor robots for telecommunication network coverage area expansion in disaster area,” in SICE Annual Conference (SICE), 2012 Proceedings of, 2012, pp. 2256–2261.
[5]   J. Fink, N. Michael, S. Kim, and V. Kumar, “Planning and control for cooperative manipulation and transportation with aerial robots,” Int. J. Rob. Res., vol. 30, no. 3, pp. 324–334, 2011.
[6]   M. Fadhil et al., “Circular Leader-Follower Formation Control of Quad-Rotor Aerial Vehicles,” vol. 25, no. 1, 2013.
[7]   D. A. Mercado, R. Castro, and R. Lozano, “Quadrotors flight formation control using a leader-follower approach,” in Control Conference (ECC), 2013 European, 2013, pp. 3858–3863.
[8]   F. Rinaldi, S. Chiesa, and F. Quagliotti, “Linear quadratic control for quadrotors UAVs dynamics and formation flight,” J. Intell. Robot. Syst., vol. 70, no. 1–4, pp. 203–220, 2013.
[9]   V. Roldão, R. Cunha, D. Cabecinhas, C. Silvestre, and P. Oliveira, “A novel leader-following strategy applied to formations of quadrotors,” in Control Conference (ECC), 2013 European, 2013, pp. 1817–1822.
[10] C. K. Peterson and J. Barton, “Virtual structure formations of cooperating UAVs using wind-compensation command generation and generalized velocity obstacles,” in Aerospace Conference, 2015 IEEE, 2015, pp. 1–7.
[11] W. Ren and R. Beard, “Decentralized scheme for spacecraft formation flying via the virtual structure approach,” J. Guid. Control. Dyn., vol. 27, no. 1, pp. 73–82, 2004.
[12] T. Paul, T. R. Krogstad, and J. T. Gravdahl, “Modelling of UAV formation flight using 3D potential field,” Simul. Model. Pract. Theory, vol. 16, no. 9, pp. 1453–1462, 2008.
[13] L. Garcia-Delgado, A. Dzul, V. Santibáñez, and M. Llama, “Quad-rotors formation based on potential functions with obstacle avoidance,” IET Control Theory Appl., vol. 6, no. 12, pp. 1787–1802, 2012.
[14] S. Kim and Y. Kim, “Three dimensional optimum controller for multiple UAV formation flight using behavior-based decentralized approach,” in Control, Automation and Systems, 2007. ICCAS’07. International Conference on, 2007, pp. 1387–1392.
[15] J. Ghommam, H. Mehrjerdi, and M. Saad, “Coordinated path-following control for a group of mobile robots with velocity recovery,” Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng., vol. 224, no. 8, pp. 995–1006, 2010.
[16] A. Fujimori, H. Kubota, N. Shibata, and Y. Tezuka, “Leader–follower formation control with obstacle avoidance using sonar-equipped mobile robots,” Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng., vol. 228, no. 5, pp. 303–315, 2014.
[17] Y. Li, J. Gao, X. Su, and J. Zhao, “Cooperation control of multiple miniature robots in unknown obstacle environment,” Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng., p. 0959651814560422, 2014.
[18] A. Ashrafi, M. Mortazavi, A. Askari, and A. Gholami, “Leader-follower formation control oF UAVs by PID-fuzzy,” AST J., vol. 3, pp. 29–40, 2017.
[19] E. Zibaei and M. A. Amiri Atashgah, “A Behavior-Based Approach To Simultaneous Realization of Leader-Following and Obstacle-Avoidance Behaviours for A Flying Robot,” Sharif Journals, Mech. Eng., vol. 34, no. 3, pp. 73–85, 2018.
[20] A. Mohammadi, E. Abbasi, M. Ghayour, and M. Danesh, “Formation Control and Path Tracking for a Group of Quadrotors to Carry Out a Suspended Load,” Modares Mech. Eng., vol. 19, no. 4, 2019.
[21] A. Nagaty, S. Saeedi, C. Thibault, M. Seto, and H. Li, “Control and navigation framework for quadrotor helicopters,” J. Intell. Robot. Syst., vol. 70, no. 1–4, pp. 1–12, 2013.
[22] F. Kendoul, I. Fantoni, and R. Lozano, “Asymptotic stability of hierarchical inner-outer loop-based flight controllers,” in Proceedings of the 17th IFAC world congress, 2008, pp. 1741–1746.
[23] C. Balas, “Modelling and linear control of a quadrotor,” Cranf. Unicersity, MSc Thesis, vol. 2007, 2006.
[24] S. Bouabdallah, “Design and control of quadrotors with application to autonomous flying.” École Polytechnique federale de Lausanne, 2007.
[25] N. Michael, D. Mellinger, Q. Lindsey, and V. Kumar, “The grasp multiple micro-uav testbed,” Robot. Autom. Mag. IEEE, vol. 17, no. 3, pp. 56–65, 2010.