Qualitative Evaluation of Flight Controller Performances for Autonomous Quadrotors

Part of the Topics in Intelligent Engineering and Informatics book series (TIEI, volume 3)

Abstract

The paper regards to benchmarking and qualitative evaluation of different autonomous quadrotor flight controllers. Three characteristic representatives of frequently used flight control techniques are considered: PID, backstepping and fuzzy. The paper aims to contribute to the objective assessment of quadrotor control performances with respect to the criteria regarding to dynamic performances, trajectory tracking precision, energy efficiency and control robustness upon stochastic internal and/or external perturbation. Qualitative evaluation of the closed-loop system performance should enable the best choice of microcopter control structure. Non-linear modeling, control and numerical simulation of two characteristic flight test-scenarios (indoor as well as outdoor) are described in the paper, too. Obtained simulation results for three representative control algorithms are graphically and table presented, analyzed and discussed.

Keywords

Autonomous quadrotor flight controller PID controller fuzzy controller 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Dzul, A., Castillo, P., Lozano, R.: Real-time stabilization and tracking of a four-rotor mini rotorcraft. IEEE Transaction on Control System Technology 12(4), 510–516 (2004)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Lozano, R., Castillo, P., Dzul, A.: Stabilization of a mini rotorcraft having four rotors. In: Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, pp. 2693–2698 (2004)Google Scholar
  3. 3.
    Palomino, A., Salazar-Cruz, S., Lozano, R.: Trajectory tracking for a four rotor mini-aircraft. In: Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005, Sevilla, Spain, pp. 2505–2510 (2005)Google Scholar
  4. 4.
    Noth, A., Bouabdallah, A., Siegwart, R.: Pid vs lq control techniques applied to an indoor micro quadrotor. In: Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 3, pp. 2451–2456 (2004)Google Scholar
  5. 5.
    Tayebi, A., McGilvray, S.: Attitude stabilization of a vtol quadrotor aircraft. IEEE Transaction on Control System Technology 14(3), 562–571 (2006)CrossRefGoogle Scholar
  6. 6.
    Fradkov, A., Andrievsky, B., Peaucelle, D.: Adaptive control experiments for laas helicopter benchmark, pp. 760–765 (2005)Google Scholar
  7. 7.
    Morel, Y., Leonessa, A.: Direct adaptive tracking control of quadrotor aerial vehicles. In: Florida Conference on Recent Advances in Robotics, pp. 1–6 (2006)Google Scholar
  8. 8.
    Lozano, R., Castillo, P., Dzul, A.: Stabilization of a mini rotorcraft with four rotors. IEEE Control Systems Magazine, 45–55 (2005)Google Scholar
  9. 9.
    Turczi, A.: Flight Control System of an Experimental Unmanned Quad-Rotor Helicopter. In: Proceedings of the 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics (2009)Google Scholar
  10. 10.
    Madani, T., Benallegue, A.: Backstepping control for a quadrotor helicopter. In: Proceedings of 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3255–3260 (2006)Google Scholar
  11. 11.
    Mokhtari, A., Benallegue, A.: Dynamic feedback controller of euler angles and wind parameters estimation for a quadrotor unmanned aerial vehicle. In: Proceedings of the 2004 IEEE International Conference on Robotics and Automation, pp. 2359–2366 (2004)Google Scholar
  12. 12.
    Benallegue, A., Mister, V., M’Sirdi, N.K.: Exact linearization and noninteracting control of a 4 rotors helicopter via dynamic feedback. In: IEEE International Workshop on Robot and Human Interactive Communication, pp. 586–593 (2001)Google Scholar
  13. 13.
    Valenti, M., Tournier, G.P., How, J.P.: Estimation and control of a quadrotor vehicle using monocular vision and moire patterns. In: AIAA Guidance, Navigation, and Control Conference and Exhibit (2006)Google Scholar
  14. 14.
    Hamel, T., Metni, N., Derkx, F.: Visual tracking control of aerial robotic systems with adaptive depth estimation. In: Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, pp. 6078–6084 (2005)Google Scholar
  15. 15.
    Ostrowski, J.P., Altug, E., Taylor, C.J.: Quadrotor control using dual camera visual feedback. In: Proceedings of the 2003 IEEE International Conference on Robotics and Automation, pp. 4294–4299 (2003)Google Scholar
  16. 16.
    Earl, M.G., D’Andrea, R.: Real-time attitude estimation techniques applied to a four rotor helicopter. In: 43rd IEEE Conference on Decision and Control, pp. 3956–3961 (2004)Google Scholar
  17. 17.
    Coza, C., Macnab, C.J.B.: A new robust adaptive-fuzzy control method applied to quadrotor helicopter stabilization (2006)Google Scholar
  18. 18.
    Tarbouchi, M., Dunfied, J., Labonte, G.: Neural network based control of a four rotor helicopter. In: 2004 IEEE Intrnational Conference on Industrial Technology, pp. 1543–1548 (2004)Google Scholar
  19. 19.
    Jang, J.S., Waslander, S.L., Hoffmann, G.M., Tomlin, C.J.: Multi-agent quadrotor testbed control design: Integral sliding mode vs. reinforcement learning. In: Proceedings of 2005 (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3712–3717 (2005)Google Scholar
  20. 20.
    Hehn, M., Ritz, R., Andrea, R.: Performance benchmarking of quadrotor systems using time-optimal control. Autonomous Robots, 1–20 (2012), doi:10.1007/s10514-012-9282-3Google Scholar
  21. 21.
    Bresciani, T.: Modelling, Identification and Control of a Quadrotor Helicopter. MSc Dissertation, Department of Automatic Control, Lund University (2008)Google Scholar
  22. 22.
    Rodic, A., Mester, G.: The Modeling and imulation of an Autonomous Quad-Rotor Microcopter n a Virtual Outdoor Scenario. Acta Polytechnica Hungarica 8(4), 107–122 (2011)Google Scholar
  23. 23.
    Rodic, A., Mester, G.: Modeling and Simulation of Quad-rotor Dynamics and Spatial Navigation. In: Proceedings of the SISY 2011, 9th IEEE International Symposium on Intelligent Systems and Informatics, Subotica, Serbia, pp. 23–28 (2011), doi:10.1109/SISY.2011.6034325Google Scholar
  24. 24.
    Bouabdallah, S., Siegwart, R.: Backstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation ICRA 2005, pp. 2247–2252 (2005)Google Scholar
  25. 25.
    Raza, S.A., Gueaieb, W.: Intelligent Flight Control of an Autonomous Quadrotor. In: Casolo, F. (ed.) InTech (2010) ISBN: 978-953-7619-55-8Google Scholar
  26. 26.
    Santos, M., Lopez, V., Morata, F.: Intelligen fuzzy controller of a quadrotor. In: Intrernational Conference on Intelligent Systems and Knowledge Engineering, ISKE 2010, pp. 141–146 (2010)Google Scholar
  27. 27.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Aleksandar Rodić
    • 1
  • Gyula Mester
    • 2
  • Ivan Stojković
    • 1
  1. 1.Robotics LaboratoryMihajlo Pupin InstituteBelgradeSerbia
  2. 2.Faculty of EngineeringUniversity of SzegedSzegedHungary

Personalised recommendations