Skip to main content
Log in

An Adaptive Dynamic Controller for Quadrotor to Perform Trajectory Tracking Tasks

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

This work proposes an adaptive dynamic controller to guide an unmanned aerial vehicle (UAV) when accomplishing trajectory tracking tasks. The controller structure consists of a kinematic controller that generates reference commands to a dynamic compensator in charge of changing the reference commands according to the system dynamics. The final control actions thus generated are then sent to the UAV to make it to track an arbitrary trajectory in the 3D space. The parameters of the dynamic compensator are directly updated during navigation, configuring a directly updated self-tuning regulator with input error, aiming at reducing the tracking errors, thus improving the system performance in task accomplishment. After describing the control system thus designed, its stability is proved using the Lyapunov theory. To validate the proposed system simulations and real experiments were run, some of them are reported here, whose results demonstrate the effectiveness of the proposed control system and its good performance, even when the initial values of the parameters associated to the dynamic model of the UAV are completely unknown. One of the conclusions, regarding the results obtained, is that the proposed system can be used as if it were an on-line identification subsystem, since the parameters converge to values that effectively represent the UAV dynamics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Achtelik, M., Bierling, T., Wang, J., Höcht, L., Holzapfel, F.: Adaptive Control of a Quadcopter in the Presence of Large/Complete Parameter Uncertainties. In: Infotech@Aerospace 2011. American Institute of Aeronautics and Astronautics, St. Louis, MI, USA (2011). https://doi.org/10.2514/6.2011-1485

  2. Alvarenga, J., Vitzilaios, N.I., Valavanis, K.P., Rutherford, M.J.: Survey of unmanned helicopter model-based navigation and control techniques. J. Intell. Robot. Syst. 80(1), 87–138 (2015)

    Article  Google Scholar 

  3. Bouadi, H., Cunha, S.S., Drouin, A., Mora-Camino, F.: Adaptive Sliding Mode Control for Quadrotor Attitude Stabilization and Altitude Tracking. In: 2011 IEEE 12Th International Symposium on Computational Intelligence and Informatics (CINTI), pp. 449–455 (2011). https://doi.org/10.1109/CINTI.2011.6108547

  4. Efe, M.O.: Robust Low Altitude Behavior Control of a Quadrotor Rotorcraft through Sliding Modes. In: 2007 Mediterranean Conference on Control Automation, pp. 1–6, Athens, Greece (2007). https://doi.org/10.1109/MED.2007.4433755

  5. Emran, B., Yesildirek, A.: Robust nonlinear composite adaptive control of quadrotor. Int. J. Digital Inform. Wirel. Commun. 4, 213–225 (2014)

    Google Scholar 

  6. Felix, M.C.: A Two Level Non Linear Inverse Control Structure for Rotorcraft Trajectory Tracking. In: 2007 Chinese Control Conference, pp. 321–325 (2007). https://doi.org/10.1109/CHICC.2006.4347095

  7. Gurdan, D., Stumpf, J., Achtelik, M., Doth, K.M., Hirzinger, G., Rus, D.: Energy-Efficient Autonomous Four-Rotor Flying Robot Controlled at 1 Khz. In: Proceedings 2007 IEEE International Conference on Robotics and Automation, pp. 361–366 (2007). https://doi.org/10.1109/ROBOT.2007.363813

  8. Hatamleh, K.S., Ma, O., Paz, R.: A uav model parameter identification method: a simulation study. Int. J. Inform. Acquis. 06(04), 225–238 (2009)

    Article  Google Scholar 

  9. Hoffer, N.V., Coopmans, C., Jensen, A.M., Chen, Y.: A survey and categorization of small low-cost unmanned aerial vehicle system identification. J. Intell. Robot. Syst. 74(1-2), 129–145 (2014)

    Article  Google Scholar 

  10. Khalil, H.K.: Nonlinear Control. Pearson, London (2015)

    Google Scholar 

  11. Krajník, T., Vonásek, V., Fiser, D., Faigl, J.: Ar-drone as a robotic platform for research and education. In: International Conference on Research and Education in Robotics - EUROBOT 2011. Prague, Czech Republic (2011). https://doi.org/10.1007/978-3-642-21975-7_16

  12. Liu, H., Xi, J., Zhong, Y.: Robust attitude stabilization for nonlinear quadrotor systems with uncertainties and delays. IEEE Trans. Ind. Electron. 64(7), 5585–5594 (2017)

    Article  Google Scholar 

  13. Madani, T., Benallegue, A.: Control of a Quadrotor Mini-Helicopter via Full State Backstepping Technique. In: Proceedings of the 45Th IEEE Conference on Decision and Control, pp. 1515–1520 (2006). https://doi.org/10.1109/CDC.2006.377548

  14. Martins, F.N., Celeste, W.C., Carelli, R., Sarcinelli-Filho, M., Bastos-Filho, T.F.: An adaptive dynamic controller for autonomous mobile robot trajectory tracking. Control. Eng. Pract. 16(11), 1354–1363 (2008)

    Article  Google Scholar 

  15. 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)

    Article  Google Scholar 

  16. Santana, L.V., Brandão, A.S., Sarcinelli-Filho, M.: Navigation and cooperative control using the ar.drone quadrotor. J. Intell. Robot. Syst. 84(1–4), 327–350 (2016). https://doi.org/10.1007/s10846-016-0355-y

    Article  Google Scholar 

  17. Santos, M., Santana, L., Brandao, A., Sarcinelli-Filho, M.: Uav Obstacle Avoidance Using Rgb-D System. In: 2015 International Conference On Unmanned Aircraft Systems (ICUAS), pp. 312–319 (2015). https://doi.org/10.1109/ICUAS.2015.7152305

  18. Santos, M., Santana, L., Martins, M., Brandao, A., Sarcinelli-Filho, M.: Estimating and Controlling Uav Position Using Rgb-D/Imu Data Fusion with Decentralized Information/Kalman Filter. In: 2015 IEEE International Conference on Industrial Technology (ICIT), pp. 232–239 (2015). https://doi.org/10.1109/ICIT.2015.7125104

  19. Santos, M.C., Santana, L.V., Brandão, A.S., Sarcinelli-Filho, M., Carelli, R.: Indoor low-cost localization system for controlling aerial robots. Control. Eng. Pract. 61, 93–111 (2017)

    Article  Google Scholar 

  20. Santos, M.C.P., Rosales, C.D., Sarcinelli-Filho, M., Carelli, R.: A novel null-space-based uav trajectory tracking controller with collision avoidance. IEEE/ASME Trans. Mechatron. 22(6), 2543–2553 (2017)

    Article  Google Scholar 

  21. Santoso, F., Garratt, M.A., Anavatti, S.G.: Adaptive Neuro-Fuzzy Inference System Identification for the Dynamics of the Ar.Drone Quadcopter. In: 2016 International Conference on Sustainable Energy Engineering and Application (ICSEEA), pp. 55–60 (2016). https://doi.org/10.1109/ICSEEA.2016.7873567

  22. Sastry, S., Bodson, M.: Adaptive Control: Stability, Convergence and Robustness. Courier Corporation, North Chelmsford (2011)

    MATH  Google Scholar 

  23. Zha, C., Ding, X., Yu, Y., Wang, X.: Quaternion-based nonlinear trajectory tracking control of a quadrotor unmanned aerial vehicle. Chinese J. Mech. Eng. 30(1), 77–92 (2017)

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank CNPq – Conselho Nacional de Desenvolvimento Científico e Tecnológico, an agency of the Brazilian Ministry of Science and Technology to support scientific and technological development –, FAPES – Fundação de Amparo à Pesquisa e Inovação do Espírito Santo, the agency of the State of Espírito Santo that supports scientific and technological development –, for the financial support to this work. They also thank CAPES – Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, an agency of the Brazilian Ministry of Education to support high education –, for the scholarship granted to Mr. Santos, the Federal Institute of Espírito Santo, the Federal University of Espírito Santo and the Institute of Automatics of the National University of San Juan, Argentine, and CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas), Argentina for supporting the development of this research. A short version of this paper was presented in ICUAS 2017.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Milton Cesar Paes Santos.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Santos, M.C.P., Rosales, C.D., Sarapura, J.A. et al. An Adaptive Dynamic Controller for Quadrotor to Perform Trajectory Tracking Tasks. J Intell Robot Syst 93, 5–16 (2019). https://doi.org/10.1007/s10846-018-0799-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-018-0799-3

Keywords

Navigation