Journal of Intelligent & Robotic Systems

, Volume 93, Issue 1–2, pp 101–111 | Cite as

Spatial Modeling and Robust Flight Control Based on Adaptive Sliding Mode Approach for a Quadrotor MAV

  • Herman CastañedaEmail author
  • J. L. Gordillo


This paper addresses the design of a robust flight control for a quadrotor micro aerial vehicle under external perturbations. The spatial vectors convention is implemented in order to represent the mathematical model of the system. Then, a flight control based on an adaptive second order sliding mode technique is designed. This controller allows to mitigate matched and bounded perturbations/uncertainties with unknown bounds, while non overstimating of the control gain; its adaptive gains permit to reduce the control effort as well as the chattering effect. Furthermore, a closed loop analysis under perturbations is given. Simulation results include a comparison between the proposed adaptive flight control against a second order sliding mode approach showing the feasibility and attractiveness of strategy.


Quadrotor MAVs Adaptive sliding mode control Robust control Sliding mode control Spatial modeling 


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This paper was a short version of the one presented in ICUAS 2017. Additionally, this work was part of a Postdoctoral stay at the Robotics National Laboratory of the ITESM-CONACyT.


  1. 1.
    Cai, G., Dias, J., Seneviratne, L.: A survey of small-scale unmanned aerial vehicles: recent advances and future development trends. Unmanned Syst. 2(2), 175–199 (2014)CrossRefGoogle Scholar
  2. 2.
    Mohd, M.A., Husain, A.R., Danapalasingam, K.A.: Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle. J. Intell. Robot. Syst. 79(2), 295–321 (2015)CrossRefGoogle Scholar
  3. 3.
    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
  4. 4.
    Satici, A.C., Poonawala, H., Spong, M.W.: Robust optimal control of quadrotor UAVs. IEEE Access 1 (1), 79–93 (2013)CrossRefGoogle Scholar
  5. 5.
    Gautam, D., Ha, C.: Control of a quadrotor using a smart self-tuning fuzzy PID controller. Int. J. Adv. Robot. Syst. 10(11), 1–9 (2013)CrossRefGoogle Scholar
  6. 6.
    Xiong, J., Zhang, G.: Global fast dynamical terminal sliding mode control for a quadrotor UAV. ISA Transactions. (2016).
  7. 7.
    Xiong, J., Zheng, E.: Position and attitude tracking control for a quadrotor UAV. ISA Trans. 53, 725–731 (2014)CrossRefGoogle Scholar
  8. 8.
    Zheng, E., Xiong, J., Luo, J.: Second order sliding mode control for a quadrotor UAV. ISA Trans. 53, 1350–1356 (2014)CrossRefGoogle Scholar
  9. 9.
    Besnard, L., Shtessel, Y., Landrum, B.: Quadrotor vehicle control via sliding mode controller driven by sliding mode disturbance observer. J. Frankl. Inst. 349, 658–684 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Luque-Vega, L., Castillo-Toledo, B., Loukianov, A.: Robust block second order sliding mode control for a quadrotor. J. Frankl. Inst. 349, 719–739 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Rida, M., Cherki, B.: A new robust control for minirotorcraft unmanned aerial vehicles. ISA Trans. 56, 86–101 (2014)Google Scholar
  12. 12.
    Ramirez, H., Parra, V., Sanchez, A., Garcia, O.: Robust backstepping control based on integral sliding modes for tracking of quadrotors. J. Intell. Robot. Syst. 73, 51–66 (2014)CrossRefGoogle Scholar
  13. 13.
    Sumantri, B., Uchiyama, N., Sano, S.: Generalized super-twisting sliding mode control with a nonlinear sliding surface for robust and energy-efficient controller of a quad-rotor helicopter. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. (2016).
  14. 14.
    Villanueva, A., Castillo-Toledo, B., et al.: System for a Quadrotor (2015)Google Scholar
  15. 15.
    Derafa, L., Benallegue, A., Fridman, L.: Super twisting control algorithm for the attitude tracking of a four rotors UAV. J. Frankl. Inst. 349, 685–689 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Ibarra, E., Castillo, P.: Nonlinear super twisting algoritmh for UAV attitude stabilization (2017)Google Scholar
  17. 17.
    Castañeda, H., Gordillo, J.L.: Spatial modeling, identification and adaptive second order sliding mode control of a micro air vehicle. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS) Miami, FL, USA, June 13–16 (2017)Google Scholar
  18. 18.
    Phang, S.K., Li, K., Yu, K.H., et al.: Systematic design and implementation of a micro unmanned quadrotor system. Unmanned Syst. 2(2), 121–141 (2014)CrossRefGoogle Scholar
  19. 19.
    Mellinger, D., Michael, N., Kumar, V.: Trajectory generation and control for precise aggressive maneuvers with quadrotors. Int. J. Robot. Res. 31(5), 664–674 (2012)CrossRefGoogle Scholar
  20. 20.
    Moreno, J., Osorio, M.: Strict Lyapunov Functions for the Super-Twisting Algorithm. IEEE Trans. Autom. Control 57(4), 1035–1040 (2012)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Tecnologico de Monterrey, Escuela de Ingenieria y CienciasMonterreyMéxico

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