The Application of Model Reference ADRC Based on PD Gain Adaptive Regulation in Quadrotor UAV

Abstract:

Unmodeled dynamics, internal disturbance and external disturbance in the quadrotor UAV kinetic model, affect the flight control and increase control complexity. In order to improve the dynamic performance and robustness of the control system, we adopt model reference ADRC based on PD gain adaptive regulation. Model reference ADRC based on PD gain adaptive regulation is able to detect changes of the controlled object, and adjust the controller parameters based on changes to achieve the stability of the control. Simulation results show that the method has a better tracking performance, better stability of the control strategy. The system can be used in engineering development and application .

• Periodical: Applied Mechanics and Materials (Volumes 347-350)
• Pages: 401-405
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.347-350.401
• Online since: August 2013
• Authors: Hong Jun Wang, Xiao Hui Qi
• Keywords: Adaptive Control, Attitude Control, PD Gain Adaptive, Quadrotor

References

[1] Raza, Syed Ali Design and control of a quadrotor unmanned aerial vehicle. Master degree, University of Ottawa (Canada), (2010).

[2] LIfang Xu, Shouda Jiang. Research of Intelligence Control for Flying Atltitude of Four Rotors Flyer. International Conference on Artificial Intelligence and Computational Intelligence, 2010, pp.294-298.

DOI: 10.1109/aici.2010.184

[3] Holger Voos. Nonlinear and Neural Network-based Control of a Small Four-Rotor Aerial Robot. International Conference on Advanced Intelligent Mechatronics. 2007, pp.1-6.

DOI: 10.1109/aim.2007.4412470

[4] Keigo  Fujimoto, Makoto  Yokoyama, Yuji  Tanab. I&I-based Adaptive control of a four-rotor mini helicopter. 36th Annual Conference on IEEE Industrial Electronics Society, 2010, pp.144-149.

DOI: 10.1109/iecon.2010.5675184

[5] Huanye Liu , Jian Li, Jianguo Yao, Fei Hu. Backstepping Based Adaptive Control for a Mini Rotorcraft with Four Rotors. Second International Conference on Computer Modeling and Simulation, 2010, pp.472-476.

DOI: 10.1109/iccms.2010.183

[6] McKerrow, P. Modelling the Dragon-flyer four-rotor helicopter. Proceedings of the 2004 IEEE International Conference on Robotics and Automation, vol. 4, pp.3596-3601, April 26-May 1, (2004).

DOI: 10.1109/robot.2004.1308810

[7] A. Benallegue and A. Mokhtari, High-order sliding-mode observer for a quadrotor UAV. International Journal of Robust and Nonlinear Control, vol. 18, pp.427-440, (2008).

DOI: 10.1002/rnc.1225

[8] P. Pounds&R. Mahony,P. Hynes&J. Roberts, Design of a Four-Rotor Aerial Robot, Proc[C]. 2002 Australasian Conference on Robotics and Automation, Auckland, 27-29 November (2002).

[9] Carlo Canetta, Jonathan Chin, Sevan Mehrabian, Quadrotor Unmanned Aerial Vehicle Final Report[J], Columbia University.

[10] Pedro Castillo, Alejandro Dzul, Rogelio Lozano, Real-Time Stabilization and Tracking of a Four-Rotor Mini Rotorcraft[J], IEEE Transactions on Control Systems Technology, Vol. 12, Number 4, 510-516, July (2004).

DOI: 10.1109/tcst.2004.825052

[11] C.A. Patel S.K. Rao, A Testbed for Mini Quadrotor Unmanned Aerial Vehicle with Protective Shroud [M]. Wichita State University, Wichita, Kansas.