Abstract
In this paper an adaptive control scheme along with its simulation, and its implementation on a quadrotor are presented. Parametric and non- parametric uncertainties in the quadrotor model make it difficult to design a controller that works properly in various conditions during flight time. Decentralized adaptive controller, which is synthesized based on improved Lyapunov-based Model Reference Adaptive Control (MRAC) technique, is suggested to solve the problem. The proposed control scheme does not need knowing the value of any physical parameter for generating appropriate control signals, and retuning the controller is not required for different payloads. An accurate simulation that includes empirical dynamic model of battery, sensors, and actuators is performed to validate the stability of the closed loop system. The simulation study simplifies implementation of the controller on our real quadrotor. A practical algorithm is proposed to alleviate and accelerate the tuning of controller parameters. The controller is implemented on the quadrotor to stabilize its attitude and altitude. Simulation and experimental results demonstrate the efficiency and robustness of the proposed controller.
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Das, A., Lewis, F., Subbaro, K.: Backstepping approach for controlling a quadrotor using lagrange form dynamics. J. Intell. Robot. Syst. 56(1–2), 127–151 (2009). doi:10.1007/s10846-009-9331-0
Orsag, M., Poropat, M. Bogdan, S.: Hybrid fly-by-wire quadrotor controller. Automatika 51(1), 19–32 (2010)
Castillo, P., Dzul, A., Lozano, R.: Real-time stabilization and tracking of a four-rotor mini rotorcraft. IEEE Trans. Control Syst. Technol. 12(4), 510–516 (2004). doi:10.1109/TCST.2004.825052
Madani, T., Benallegue, A.: Adaptive control via backstepping technique and neural networks of a quadrotor helicopter. In: Proceedings of the 17th World Congress the International Federation of Automatic Control, pp. 6513–6518. Seoul, Korea (2008)
Huang, M., Xian, B., Diao, C., Yang, K., Feng, Y.: Adaptive tracking control of underactuated quadrotor unmanned aerial vehicles via backstepping. In: Proceedings of American Control Conference, pp. 2076–2081. Marriott Waterfront, Baltimore, MD, USA (2010)
Michini, B., How, J.: L1 adaptive control for indoor autonomous vehicles: design process and flight testing. In: Proceeding of AIAA Guidance, Navigation, and Control Conference, pp. 5754–5768. Chicago, Illinois (2009)
Dierks, T., jagannathan, S.: Output feedback control of a quadrotor uav using neural networks. IEEE Trans. Neural Netw. 21(1), 50–66 (2010)
Nicol, C., Macnab, C.J.B., Ramirez-Serrano, A.: Robust adaptive control of a quadrotor helicopter. J. Mechatronics 21(6), 927–938 (2011)
Zemalache, K., Maaref, H.: Controlling a drone: Comparison between a based model method and a fuzzy inference system. Appl. Soft Comput. 9, 553–562 (2009). doi:10.1016/j.asoc.2008.08.007
Raffo, G., Ortega, M., Rubio, F.: An integral predictive/nonlinear H ∞ control structure for a quadrotor helicopter. Automatica 46, 29–39 (2010). doi:10.1016/j.automatica.2009.10.018
Mhammed, G., Hicham, M.: A high gain observer and sliding mode controller for an autonomous quadrotor helicopter. Int. J. Intell. Control Syst. 14(3), 204–212 (2009)
Das, A., Lewis, F., Subbaro, K.: Dynamic inversion with zero-dynamics stabilisation for Quadrotor control. IET Control Theory Appl. 3, 303–314 (2009). doi:10.1049/iet-cta:20080002
Lee, D., Kim, H., Sastry, S.: Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter. Int. J. Control Autom. 7(3),419–428 (2009). doi:10.1007/s12555-009-0311-8
Benallegue, A., Mokhtari, A., Fridman, L.: High-order sliding-mode observer for a quadrotor UAV. Int. J. Robust Nonlinear Control 18(4–5), 427–440 (2008). doi:10.1002/rnc.1225
Zhang, R., Quan, Q., Cai, K.Y.: Attitude control of a quadrotor aircraft subject to a class of time-varying disturbances. IET Control Theory Appl. 5(9), 1140–1146 (2011). doi:10.1049/iet-cta.2010.0273
Efe, M.Ö.: Neural network assisted computationally simple PID control of a quadrotor UAV. IEEE Trans. Ind. Informat. 7(2), 354–361 (2011). doi:10.1109/TII.2011.2123906
Cano, J.M., Lo’ pez-Mart’nez, M., Rubio, F.R.: Asynchronous networked control of linear systems via L2-gain-based transformations: analysis and synthesis. IET Control Theory Appl. 5(4), 647–654 (2011). doi:10.1049/iet-cta.2010.0205
Fahimi, F, Saffarian, M.: The control point concept for nonlinear trajectory-tracking control of autonomous helicopters with fly-bar. Int. J. Control 84(2), 242–252 (2011). doi:10.1080/00207179.2010.549842
Guenard, N., Hamel, T., Mahony, R.: A practical visual servo control for an unmanned aerial vehicle. IEEE Trans. Robot. 24(2), 331–340 (2008). doi:10.1109/TRO.2008.916666
Mahony, R., Corke, P., Hamel, T.: Dynamic image-based visual servo control using centroid and optic flow features. J. Dyn. Syst. Meas. Control. 130, 35–46 (2008). doi:10.1115/1.2807085
Bourquardez, O., Mahony, R., Guenard, N., Chaumette, F., Hamel, T., Eck, L.: Image-based visual servo control of the translation kinematics of a quadrotor aerial vehicle. IEEE Trans. Robot. 25(3), 743–749 (2009). doi:10.1109/TRO.2008.2011419
Garca Carrillo, L.R., Rondon, E., Sanchez, A., Dzul, A., Lozano, R.: Stabilization and trajectory tracking of a quadrotor using vision. J. Intell. Robot. Syst. 61(1–4), 103–118 (2011). doi:10.1007/s10846-010-9472-1
Eberli, D., Scaramuzza, D., Weiss, S., Siegwart, R.: Vision based position control for mavs using one single circular landmark. J. Intell. Robot. Syst. 61(1–4), 495–512 (2011). doi:10.1007/s10846-010-9494-8
Tarhan, M., Altug, E.: EKF based attitude estimation and stabilizationof a quadrotor uav using vanishing points in catadioptric images. J. Intell. Robot. Syst. 62(3–4), 587–607 (2011). doi:10.1007/s10846-010-9459-y
Seraji, H.: Decentralized adaptive control of manipulators: theory, simulation, and experimentation. IEEE Trans. Robot. Autom. 5(2), 183–201 (1989)
Bouabdallah, S.: Design and control of quadrotor with application to autonomous flying. Unpublished Doctoral Dissertation, pp. 15–25. EPFL University, Lausanne (2007)
Asada, H., Slotine, J.: Robot Analysis and Control. Wiley, New York (1986)
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Mohammadi, M., Shahri, A.M. Adaptive Nonlinear Stabilization Control for a Quadrotor UAV: Theory, Simulation and Experimentation. J Intell Robot Syst 72, 105–122 (2013). https://doi.org/10.1007/s10846-013-9813-y
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DOI: https://doi.org/10.1007/s10846-013-9813-y