Neural Network Control for Quadrotors

Osman Çakir, Tolga Yüksel


While quadrotors are becoming more popular, their controllers should be improved. In this study, neural network control of quadrotors is aimed to obtain an artificial intelligence based controller. Firstly, the quadrotor is modeled according to quadrotor dynamics. Then, PD controllers for x, y, yaw and z control of quadrotor are implemented as classical controllers. The results for these controllers are recorded as training data of NN controllers. As the proposed controllers, NN controllers are trained according to these data and performance of these results are examined. The results verify that NN controllers achieve good trajectory tracking results.


Quadrotors; neural networks.

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P. E. I. Pounds, “Design, Construction and Control of a Large Quadrotor Micro Air Vehicle,” The Australian National University, 2007.

G. M. Hoffmann, H. Huang, S. L. Waslander, and C. J. Tomlin, “Precision flight control for a multi-vehicle quadrotor helicopter testbed,” Control Eng. Pract., vol. 19, no. 9, pp. 1023–1036, 2011.

R. Mahony, V. Kumar, and P. Corke, “Multirotor Aerial Vehicles: Modeling, Estimation, and Control of Quadrotor,” IEEE Robot. Autom. Mag., vol. 19, no. 3, pp. 20–32, 2012.

M. Santos, V. López, and F. Morata, “Intelligent fuzzy controller of a quadrotor,” Proc. 2010 IEEE Int. Conf. Intell. Syst. Knowl. Eng. ISKE 2010, pp. 141–146, 2010.

P. S. Bhatkhande, “Real time fuzzy controller for quadrotor stabilitiy control,” p. 58, 2014.

R. Xu and U. Ozguner, “Sliding Mode Control of a Quadrotor Helicopter,” Proc. 45th IEEE Conf. Decis. Control, pp. 4957–4962, 2006.

M. Herrera, W. Chamorro, A. P. Gomez, and O. Camacho, “Sliding Mode Control: An Approach to Control a Quadrotor,” 2015 Asia-Pacific Conf. Comput. Aided Syst. Eng., pp. 314–319, 2015.

Y. Bai, H. Liu, Z. Shi, and Y. Zhong, “Robust control of quadrotor unmanned air vehicles,” Proc. 31th Chinese Control Conf., pp. 4462–4467, 2012.

S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd ed. Upper Saddle River, NJ, USA: Prentice Hall PTR, 1998.

J. P. Antsaklis, “Neural Networks for Control Systems,” vol. 1, no. 2, pp. 242–244, 1990.

F. Lewis and S. Ge, “Neural networks in feedback control systems,” Mech. Eng. Handbook. Wiley …, pp. 1–28, 2005.

P. I. Corke, Robotics, Vision & Control: Fundamental Algorithms in Matlab. Springer US, 2011.

MathWorks, “Neural Network Toolbox.” [Online]. Available:


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