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On-line aerodynamic identification of quadrotor and its application to tracking control

On-line aerodynamic identification of quadrotor and its application to tracking control

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This study investigates the aerodynamic effects and the tracking control problem of quadrotor-type unmanned aerial vehicles. The authors first present the on-line identification of the aerodynamic parameters by using the recursive least squares algorithm based on the measurement outputs of the accelerometer. Then, the non-linear discrete-time trajectory tracking controllers with aerodynamic compensation have been designed. Through identifying and compensating the external aerodynamics on line, the simulation results show that the tracking performance has been enhanced, especially when the vehicle is in some flight envelopes where the aerodynamics have significant effects on the quadrotor dynamics, such as the large-acceleration flight regime.

References

    1. 1)
      • 1. Du, H., Li, S.: ‘Attitude synchronization control for a group of flexible spacecraft’, Automatica, 2014, 50, (2), pp. 646651.
    2. 2)
      • 2. Wang, Y.Q., Wu, Q.H., Wang, Y.: ‘Distributed consensus protocols for coordinated control of multiple quadrotors under a directed topology’, IET Control Theory Appl., 2013, 7, (14), pp. 17801792.
    3. 3)
      • 3. Purvis, K.B., Khammash, M.: ‘Estimation and optimal configurations for localization using cooperative UAVs’, IEEE Trans. Control Syst. Technol., 2008, 16, (5), pp. 947958.
    4. 4)
      • 4. Mahony, R., Kumar, V., Corke, P.: ‘Multirotor aerial vehicles: modeling, estimation, and control of quadrotor’, IEEE Robot. Autom. Mag., 2012, 19, (3), pp. 2032.
    5. 5)
      • 5. Bouabdallah, S., Siegwart, R.: ‘Full control of a quadrotor’. Proc. 2007 IEEE/RSJ Int. Conf. Intelligent Robots and Systems, San Diego, CA, October 2007, pp. 153158.
    6. 6)
      • 6. Alexis, B., Nikolakopoulos, G., Tzes, A.: ‘Model predictive quadrotor control: attitude, altitude and position experimental studies’, IET Control Theory Appl., 2012, 6, (12), pp. 18121827.
    7. 7)
      • 7. Du, H., Shen, H., Zhu, W.: ‘Control of a hovering quadrotor aircraft based finite-time attitude control algorithm’. Proc. 12th IEEE Int. Conf. Control and Automation, Kathmandu, Nepal, June 2016, pp. 192197.
    8. 8)
      • 8. Lu, H., Liu, C.J., Coombes, M., et al: ‘Online optimisation-based backstepping control design with application to quadrotor’, IET Control Theory Appl., 2016, 10, (14), pp. 16011611.
    9. 9)
      • 9. Zuo, Z., Wang, C.L.: ‘Adaptive trajectory tracking control of output constrained multi-rotors systems’, IET Control Theory Appl., 2014, 8, (13), pp. 11631174.
    10. 10)
      • 10. Zuo, Z.: ‘Trajectory tracking control design with command-filtered compensation for a quadrotor’, IET Control Theory Appl., 2010, 4, (11), pp. 23432355.
    11. 11)
      • 11. Das, A., Subbarao, K., Lewis, F.: ‘Dynamic inversion with zero-dynamics stabilisation for quadrotor control’, IET Control Theory Appl., 2009, 3, (3), pp. 303314.
    12. 12)
      • 12. Lee, D., Jim, H.K., Sastry, S.: ‘Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter’, Int. J. Control Autom. Syst., 2009, 7, (3), pp. 419428.
    13. 13)
      • 13. Omari, S., Hua, M.D., Ducard, G., et al: ‘Nonlinear control of VTOL UAVs incoporating flapping dynamics’. Proc. 2013 IEEE/RSJ Int. Conf. Intelligent Robots and Systems, Tokyo, Japan, November 2013, pp. 24192425.
    14. 14)
      • 14. Fay, G.: ‘Derivation of the aerodynamic forces for the mesicopter simulation’, Technical Report, Stanford University, Stanford, CA, 2001.
    15. 15)
      • 15. Leishman, J.G.: ‘Principles of helicopter aerodynamics’ (Cambridge University Press, Cambridge, 2000, 2nd edn., 2006).
    16. 16)
      • 16. Hoffmann, G.M., Huang, H., Waslander, S., et al: ‘Quadrotor helicopter flight dynamics and control: theory and experiment’. Proc. AIAA Guidance, Navigation and Control Conf. and Exhibit, Hilton Head, South Carolina, August 2007, pp. 120.
    17. 17)
      • 17. Huang, H., Hoffmann, G.M., Waslander, S.L., et al: ‘Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering’. Proc. 2009 IEEE Int. Conf. Robotics and Automation, Kobe, Japan, May 2009, pp. 32773282.
    18. 18)
      • 18. Kaya, D., Kutay, A.T.: ‘Aerodynamic modeling and parameter estimation of a quadrotor helicopter’. Proc. AIAA Atmospheric Flight Mechanics Conf., Atlanta, GA, June 2014, pp. 20142558.
    19. 19)
      • 19. Bangura, M., Melega, M., Naldi, R., et al: ‘Aerodynamics of rotor blades for quadrotors’, arXiv preprint, arXiv:1601.00733, 2016.
    20. 20)
      • 20. Goodwin, G.C., Sin, K.S.: ‘Adaptive filtering prediction and control’ (Prentice-Hall, New Jersey, 1984, 1st edn.).
    21. 21)
      • 21. Bangura, M., Mahony, R.: ‘Nonlinear dynamic modeling for high performance control of a quadrotor’. Proc. Australasian Conf. Robotics and Automation, Victoria University of the Wellington, New Zealand, December 2012, pp. 110.
    22. 22)
      • 22. Martin, P., Salaün, E.: ‘The true role of accelerometer feedback in quadrotor control’. Proc. 2010 IEEE Int. Conf. Robotics and Automation, Anchorage, AK, May 2010, pp. 16231629.
    23. 23)
      • 23. Metni, N., Pflimlin, J.M., Hamel, T., et al: ‘Attitude and gyro bias estimation for a VTOL UAV’, Control Eng. Pract., 2006, 14, (12), pp. 15111520.
    24. 24)
      • 24. Ma, C., Chen, M.Z.Q., Lam, J., et al: ‘Joint unscented Kalman filter for dual estimation in a bifilar pendulum for a small UAV’. Proc. 10th Asian Control Conf., Kota Kinabalu, Malaysia, May 2015, pp. 16.
    25. 25)
      • 25. Roberts, A., Tayebi, A.: ‘Adaptive position tracking of VTOL UAVs’, IEEE Trans. Robot., 2011, 27, (1), pp. 129142.
    26. 26)
      • 26. Khalil, H.K.: ‘Nonlinear system’ (Prentice-Hall, New Jersey, 1996, 3rd edn., 2002).
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