Advertisement

A Multi-Time-Scale Finite Time Controller for the Quadrotor UAVs with Uncertainties

  • Zhen ZhouEmail author
  • Hongbin Wang
  • Zhongquan Hu
  • Yueling Wang
  • Hong Wang
Article
  • 291 Downloads

Abstract

A control method with a multi-time-scale structure is proposed to perform finite time motion control of the quadrotor unmanned aerial vehicles (UAVs) with uncertainties. In order to facilitate the controller-design, finite time extended state observer (ESO) in the first and second time scales is applied to estimate the system uncertainties; the attitude controllers and the height controller are designed for finite time stabilization of the equilibriums in the third time scale; and finally, the output feedback technique is utilized to design the horizontal auxiliary controllers, meanwhile the reference angles are settled for the attitude dynamics in the fourth and slowest time scale. It allows us to analyze the system dynamics in each time scale independently, and conclusions on finite time stabilization are achieved gradually with a large region of attraction. Simulation and experimental results on the Qball2 platform are given to verify the efficacy of the strategy and establish the feasibility of implementation.

Keywords

Finite time control Extended state observer Multi-time-scale System uncertainties Quadrotor UAVs 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgments

This work is supported by NSFC under grant 61473248 and Natural Science Foundation of Hebei Province under grant F2016203496.

References

  1. 1.
    López-Estrada, F.R., Ponsart, J.C., Theilliol, D., et al.: LPV model-based tracking control and robust sensor fault diagnosis for a quadrotor UAV. J. Intell. Robot. Syst. 84(1–4), 163–177 (2016)CrossRefGoogle Scholar
  2. 2.
    Şenkul, A.F., Altuǧ, E.: System design of a novel tilt-roll rotor quadrotor UAV. J. Intell. Robot. Syst. 84(1–4), 575–599 (2016)Google Scholar
  3. 3.
    Aboutalebi, P., Abbaspour, A., Forouzannezhad, P., et al.: A novel sensor fault detection in an unmanned quadrotor based on adaptive neural observer. J. Intell. Robot. Syst. 2017, 1–12 (2017)Google Scholar
  4. 4.
    Chen, F., Lei, W., Zhang, K., et al.: A novel nonlinear resilient control for a quadrotor UAV via backstepping control and nonlinear disturbance observer. Nonlinear Dyn. 2016, 1–15 (2016)zbMATHGoogle Scholar
  5. 5.
    Tan, C.K., Wang, J., Paw, Y.C., et al.: Tracking of a moving ground target by a quadrotor using a backstepping approach based on a full state cascaded dynamics. Appl. Soft Comput. 47, 47–62 (2016)CrossRefGoogle Scholar
  6. 6.
    Dydek, Z.T., Annaswamy, A.M., Lavretsky, E.: Adaptive control of quadrotor UAVs: A design trade study with flight evaluations. IEEE Trans. Control Syst. Technol. 21(4), 1400–1406 (2013)CrossRefGoogle Scholar
  7. 7.
    Raffo, G.V., Ortega, M.G., Rubio, F.R.: An integral predictive/nonlinear H8 control structure for a quadrotor helicopter. Automatica 46(1), 29–39 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Sumantri, B., Uchiyama, N., Sano, S.: Least square based sliding mode control for a quadrotor helicopter and energy saving by chattering reduction. Mech. Syst. Signal Process. 66, 769–784 (2016)CrossRefGoogle Scholar
  9. 9.
    Xiong, J.J., Zhang, G.B.: Global fast dynamic terminal sliding mode control for a quadrotor UAV. ISA Trans., 1–8 (2016)Google Scholar
  10. 10.
    Zhao, B., Xian, B., Zhang, Y., et al.: Nonlinear robust adaptive tracking control of a quadrotor UAV via immersion and invariance methodology. IEEE Trans. Indust. Electron. 62(5), 2891–2902 (2015)CrossRefGoogle Scholar
  11. 11.
    Das, A., Subbarao, K., Lewis, F.: Dynamic inversion with zero-dynamics stabilization for quadrotor control. IET Control Theory Appl. 3(3), 303–314 (2009)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Li, S., Wang, Y., Tan, J., et al.: Adaptive RBFNNs/integral sliding mode control for a quadrotor aircraft. Neurocomputing 216, 126–134 (2016)CrossRefGoogle Scholar
  13. 13.
    Abbaspour, A., Sadati, S.H., Sadeghi, M.: Nonlinear optimized adaptive trajectory control of helicopter. Control Theory Technol. 13(4), 297–310 (2015)CrossRefzbMATHGoogle Scholar
  14. 14.
    Dierks, T., Jagannathan, S.: Output feedback control of a quadrotor UAV using neural networks. IEEE Trans. Neural Netw. 21(1), 50–66 (2010)CrossRefGoogle Scholar
  15. 15.
    Cao, N., Lynch, A.F.: Inner-outer loop control for quadrotor UAVs with input and state constraints. IEEE Trans. Control Syst. Technol. 24(5), 1797–1804 (2016)CrossRefGoogle Scholar
  16. 16.
    Zhao, B., Xian, B., Zhang, Y., et al.: Nonlinear robust sliding mode control of a quadrotor unmanned aerial vehicle based on immersion and invariance method. Int. J. Robust Nonlinear Control 25(18), 3714–3731 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Xiong, J.J., Zheng, E.H.: Position and attitude tracking control for a quadrotor UAV. ISA Trans. 53(3), 725–731 (2014)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Wang, C., Song, B., Huang, P., et al.: Trajectory tracking control for quadrotor robot subject to payload variation and wind gust disturbance. J. Intell. Robot. Syst. 83(2), 315–333 (2016)CrossRefGoogle Scholar
  19. 19.
    Xian, B., Diao, C., Zhao, B., et al.: Nonlinear robust output feedback tracking control of a quadrotor UAV using quaternion representation. Nonlinear Dyn. 79(4), 2735–2752 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Mohammadi, M., Shahri, A.M.: Adaptive nonlinear stabilization control for a quadrotor UAV: Theory, simulation and experimentation. J. Intell. Robot. Syst. 72(1), 105–122 (2013)CrossRefGoogle Scholar
  21. 21.
    Dong, W., Gu, G.Y., Zhu, X., et al.: A high-performance flight control approach for quadrotors using a modified active disturbance rejection technique. Robot. Auton. Syst. 83, 177–187 (2016)CrossRefGoogle Scholar
  22. 22.
    Pérez-Alcocer, R., Moreno-Valenzuela, J., Miranda-Colorado, R.: A robust approach for trajectory tracking control of a quadrotor with experimental validation. ISA Trans. 65, 262–274 (2016)CrossRefGoogle Scholar
  23. 23.
    Lee, J., Mukherjee, R., Khalil, H.K.: Output feedback stabilization of inverted pendulum on a cart in the presence of uncertainties. Automatica 54, 146–157 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  24. 24.
    Ravichandran, M.T., Mahindrakar, A.D.: Robust stabilization of a class of underactuated mechanical systems using time scaling and Lyapunov redesign. IEEE Trans. Indust. Electron. 58(9), 4299–4313 (2011)CrossRefGoogle Scholar
  25. 25.
    González-Vázquez, S., Moreno-Valenzuela, J.: Motion control of a quadrotor aircraft via singular perturbations. Int. J. Adv. Robot. Syst 10(10), 1–16 (2013)CrossRefGoogle Scholar
  26. 26.
    Izaguirre-Espinosa, C., Muñoz-Vázquez, A.J., Sánchez-Orta, A., et al.: Attitude control of quadrotors based on fractional sliding modes: theory and experiments. IET Control Theory Appl. 10(7), 825–832 (2016)MathSciNetCrossRefGoogle Scholar
  27. 27.
    Wang, H., Zhou, Z., Hao, C., et al.: FTESO-based finite time control for underactuated system within a bound input. Asian J. Control (2018)Google Scholar
  28. 28.
    Tan, C.P., Yu, X., Man, Z.: Terminal sliding mode observers for a class of nonlinear systems. Automatica 46(8), 1401–1404 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  29. 29.
    Shen, Y., Huang, Y., Gu, J.: Global finite-time observers for Lipschitz nonlinear systems. IEEE Trans. Autom. Control 56(2), 418–424 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  30. 30.
    Su, Y., Zheng, C.: Robust finite-time output feedback control of perturbed double integrator. Automatica 60, 86–91 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  31. 31.
    Bhat, S.P., Bernstein, D.S.: Continuous finite-time stabilization of the translational and rotational double integrators. IEEE Trans. Autom. Control 43(5), 678–682 (1998)MathSciNetCrossRefzbMATHGoogle Scholar
  32. 32.
    Bhat, S.P., Bernstein, D.S.: Geometric homogeneity with applications to finite-time stability. Math. Control Signals Syst. 17(2), 101–127 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  33. 33.
    Li, S., Ding, S., Tian, Y.: A finite-time state feedback stabilization method for a class of second order nonlinear systems. Acta Automat. Sinica 33(1), 101–104 (2007)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Yu, S., Yu, X., Shirinzadeh, B., et al.: Continuous finite-time control for robotic manipulators with terminal sliding mode. Automatica 41(11), 1957–1964 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  35. 35.
    Quanser: User Manual Qball 2 for QUARC. Set up and Configuration (2014)Google Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Lab of Industrial Computer Control Engineering of Hebei ProvinceYanshan UniversityQinhuangdaoChina

Personalised recommendations