Feedforward Control of an Autonomous Helicopter

  • A. Danapalasingam, Kumeresan (Projektdeltager)
  • la Cour-Harbo, Anders (Andet)



It is an acknowledged fact in the field of engineering that autonomous helicopters are realizable. This is evident as many researches in the matured area of autonomous helicopters have reported the success of autonomous flight [1], [2], [3]. Numerous types of control algorithms have been applied successfully to enable satisfactory autonomous flight performance such as Model Reference Adaptive Control with Artificial Neural Networks [2], [4], Model Predictive Control [3], Linear Quadratic with Integral Control [5], Fuzzy tuned PI Control [6] and a spectrum of other classical and modern control techniques. However, all these reports either did not point out the robustness of their systems against external disturbances, or assumed that they could handle the unmeasured disturbances to a certain extent. To be precise, there has been no apparent research in autonomous helicopters addressing the capability of the helicopters performing satisfactory flight in harsh weather conditions. To effectively solve this problem, one of the methods would involve modelling the dynamics of the wind disturbances (weather condition to be considered) and applying a feed forward controller to suppress the effects of the measured disturbances (wind). 


[1]     Min Zhu, Ming Liu, WenBing Chen, FuCheng He, "Autonomous helicopter navigating and tracking with stereo-vision in IIM-USTC", on Systems and Control in Aerospace and Astronautics 1st International Symposium, 2006, pp. 1388-1391.  

[2]     Eric N. Johnson, Anthony J. Calise, Hesham A. El-Shirbiny, and Rolf T. Rysdyk, "Feedback linearization with neural network augmentation applied to X-33 attitude control", in AIAA Guidance, Navigation and Control Conference, August 2000.

[3]     D. Shim, H. Chung, H. J. Kim, S. Sastry, "Autonomous exploration in unknown urban environments for unmanned aerial vehicles," in AIAA Guidance, Navigation and Control Conference, August 2005.

[4]     Anthony J. Calise and Rolf T. Rysdyk, "Nonlinear adaptive flight control using neural networks", IEEE Control Systems Magazine,Volume 18,  Issue 6,  pp. 14 - 25, December 1998.

[5]     Zhenyu Yu, Demian Celestino and Kenzo Nonami, "Development of 3D vision enabled small-scale autonomous helicopter", on Intelligent Robots and Systems IEEE/RSJ International Conference, October 2006, pp. 2912-2917.

[6]     Yu Xu, Ping Li, Bo Han and Qinyuan Ren, "Intelligent rotor speed controller for a mini autonomous helicopter", on Intelligent Robots and Systems International Conference, October 2006, pp. 2918-2923.  

Effektiv start/slut dato15/02/200715/02/2010


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    • Nonlinear Feedforward Control for Wind Disturbance Rejection on Autonomous Helicopter

      Bisgaard, M., la Cour-Harbo, A. & A. Danapalasingam, K., 2010, IEEE/RSJ International Conference on Intelligent Robots and Systems: Proceedings. IEEE Press, s. 1078 - 1083 (I E E E International Conference on Intelligent Robots and Systems. Proceedings).

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