Design, Implementation, and Flight Tests of a Feedback Linearization Controller for Multirotor UAVs

  • Received : 2017.08.17
  • Accepted : 2017.11.22
  • Published : 2017.12.30


This paper proposes a feedback-linearization-based control algorithm for multirotor unmanned aerial vehicles (UAVs). The feedback linearization scheme is highly efficient for considering nonlinearity between the rotational and translational motion of multirotor UAVs. We also propose a dynamic equation that reflects the aerodynamic effects of the vehicles; the equation's parameters can be determined through curve fitting using actual flight data. We derive the feedback linearization controller from the proposed dynamic equation, and propose a Luenberger observer to attenuate measurement noises. The proposed algorithm is implemented using our in-house flight control computer, and we describe its implementation in detail. To investigate the performance of the proposed algorithm, we carry out two flight scenarios: the first scenario, an autonomous landing on a moving platform, is a test of maneuverability; the second, picking up and replacing an object, test the algorithm's accuracy. In these scenarios, the proposed algorithm precisely controls multirotor UAVs, and we confirm that it can be successfully applied to real flight environments.


Supported by : Agency for Defense Development


  1. Wei, W., Cohen, K. and Tischler, M. B., "System Identification and Controller Optimization of a Quadrotor UAV", Proceedings of the AHS International's 71st Annual Forum and Technology Display, Virginia, USA, 2015.
  2. Szafranski, G. and Czyba, R., "Different Approaches of PID Control UAV Type Quadrotor", Proceedings of the International Micro Air Vehicles Conference 2011 Summer Edition, 't Harde, Netherlands, 2011.
  3. Li, J. and Li, Y., "Dynamic Analysis and PID Control for a Quadrotor", Proceedings of the 2011 IEEE International Conference on Mechatronics and Automation, Beijing, China, 2011.
  4. Khatoon, S., Gupta, D. and Das, L. K., "PID & LQR Control for a Quadrotor: Modeling and Simulation", Proceedings of 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), New Delhi, India, 2014.
  5. Reyes-Valeria, E., Enriquez-Caldera, R., Camacho- Lara, S. and Guichard, J., "LQR Control for a Quadrotor Using unit Quaternions: Modeling and Simulation", Proceedings of the International Conference on Electronics, Communications and Computing, Cholula, Mexico, 2013.
  6. Lee, B. Y., Yoo, D. W. and Tahk, M. J., "Performance Comparison of Three Different Types of Attitude Control Systems of the Quad-Rotor UAV to Perform Flip Maneuver", International Journal of Aeronautical and Space Sciences, Vol. 14, No. 1, 2013, pp. 58-66. DOI: 10.5139/IJASS.2013.14.1.58
  7. Chen, X. J. and Li, D., "Modeling and Designing Intelligent Adaptive Sliding Mode Controller for an Eight-Rotor MAV", International Journal of Aeronautical and Space Sciences, Vol. 14, No. 2, 2013, pp. 172-182. DOI: 10.5139/IJASS.2013.14.2.172
  8. Lee, D., Kim, H. J. and Sastry, S., "Feedback Linearization vs. Adaptive Sliding Mode Control for a Quadrotor Helicopter", International Journal of Control, Automation and Systems, Vol. 7, No. 3, 2009, pp. 419-428. DOI: 10.1007/s12555-009-0311-8
  9. Huo, X., Huo, M. and Karimi, H. R., "Attitude Stabilization Control of a Quadrotor UAV by Using Backstepping Approach", Mathematical Problems in Engineering, Vol. 2014, Article ID 749803, 9 pages. DOI: 10.1155/2014/749803
  10. Dydek, Z. T., Annaswamy, A. M. and Lavretsky, E., "Adaptive Control of Quadrotor UAVs: A Design Trade Study with Flight Evaluations", IEEE Transactions on Control Systems Technology, Vol. 21, Issue 4, 2013, pp. 1400-1406. DOI: 10.1109/TCST.2012.2200104
  11. Sanz, R., Garcia, P., Zhong, Q. C. and Albertos, P., "Robust Control of Quadrotors Based on an Uncertainty and Disturbance Estimator", Journal of Dynamic Systems, Measurement, and Control, Vol. 138, Issue 7, 2016, DS-15-1035. DOI: 10.1115/1.4033315
  12. Yang, Y. and Yan, Y., "Attitude Regulation for Unmanned Quadrotors Using Adaptive Fuzzy Gain-Scheduling Sliding Mode Control", Journal of Aerospace Science and Technology, Vol. 54, 2016, pp. 208-217. DOI: 10.1016/j.ast.2016.04.005
  13. Dierks, T. and Jagannathan, S., "Output Feedback Control of a Quadrotor UAV Using Neural Networks", IEEE Transactions on Neural Networks, Vol. 21, No. 1, 2010, pp. 50-66. DOI: 10.1109/TNN.2009.2034145
  14. Park, S., "Autonomous Aerobatics on Commanded Path", Aerospace Science and Technology, Vol. 22, Issue 1, 2012, pp. 64-74. DOI: 10.1016/j.ast.2011.06.007
  15. Cho, N., Kim, Y. and Park, S., "Three-Dimensional Nonlinear Differential Geometric Path-Following Guidance Law", Journal of Guidance, Control, and Dynamics, Vol. 38, No. 12, 2015, pp. 2366-2384. DOI: 10.2514/1.G001060
  16. Khalil, H. K., Nonlinear Systems, 3rd Edition, Pearson, 2002.
  17. Al-Hiddabi, S. A., "Quadrotor Control Using Feedback Linearization with Dynamic Extension", Proceedings of the 2009 6th International Symposium on Mechatronics and its Applications, Sharjah, UAE, 2009.
  18. Voos, H., "Nonlinear Control of a Quadrotor Micro- Uav Using Feedback-Linearization", Proceedings of the 2009 IEEE International Conference on Mechatronics, Malaga, Spain, 2009.
  19. Mokhtari, A., M'Sirdi, N. K., Meghriche, K. and Belaidi, A., "Feedback Linearization and Linear Observer for a Quadrotor Unmanned Aerial Vehicle", Advanced Robotics, Vol. 20, No. 1, 2006, pp. 71-91. DOI:10.1163/156855306775275495
  20. Benallegue, A., Mokhtari, A. and Fridman, L., "Feedback Linearization and High Order Sliding Mode Observer for a Quadrotor UAV", Proceedings of the 2006 International Workshop on Variable Structure Systems, Alghero, Italy, 2006.
  21. Luenberger, D., "Observers for Multivariable Systems", IEEE Transactions on Automatic Control, Vol. 11, Issue 2, 1966, pp. 190-197. DOI: 10.1109/TAC.1966.1098323
  22. Radke, A. and Gao, Z., "A Survey of State and Disturbance Observers for Practitioners", Proceedings of the 2006 American Control Conference, Minnesota, USA, 2006.
  23. EAGLE,
  24. Lee, D. and Shim, D. H., "Design and Validation of Low-Cost Flight Control Computer for Multi-Rotor UAVs", Journal of The Korean Society for Aeronautical and Space Sciences, Vol. 45, No. 5, 2017, pp. 401-408. DOI: 10.5139/JKSAS.2017.45.5.401
  25. Code Composer Studio,
  26. TivaWare for C Series,
  27. System Identification Toolbox,
  28. Curve Fitting Toolbox,
  29. Lee, H., Lee, D., Cho, S., Kim, H. and Shim, D. H., "Design of Vision-Based Autonomous Landing System on the Moving Vehicle Using the UAV", Proceedings of the KSAS 2017 Spring Conference, Samcheok, Republic of Korea, 2017.

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