There are a lot of methods for the stabilization of quadcopters and the newest are based on AI. A neural network is a simplified model that imitates the human brain's processes. In the research paper, we present a neural network control model for quadcopter stabilization. A single hidden layer network model was estimated to investigate the dynamics of the UAV. A control system with a classical PID controller was used to train the neural network model. This method is used for examining how the neural network imitates the stabilization of the quadcopter in real flight mode. The novelty of the work was to design of small size 3 layers NN model that runs in real-time in a quadcopter. The PID and machine learning controllers' operation results were compared to each other and
shown in the experiment.
artificial intelligence, control system, quadrotor, neural network, unmanned aerial vehicle
 A. Zulu*, S. John, "A Review of Control Algorithms for Autonomous Quadrotors," Open Journal of Applied Sciences, 2014, 4, 547-556
 H. Boudjedir, O.Bouhali, and N. Rizoug, "Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter," International Journal of Information Technology, Control and Automation (IJITCA) Vol.2, No.3, July 2012.
 H. Boudjedir, O.Bouhali, and N. Rizoug, "Adaptive neural network control based on neural observer for quadrotor unmanned aerial vehicle," Advanced Robotics, 2014, Vol.28, No.17, 1151–1164, http://dx.doi.org/10.1080/01691864.2014.913498 .
 T. Dierks and S. Jagannathan, "Neural Network Control of Quadrotor UAV Formations," 2009 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA June 10-12, 2009.
 Holger Voos, "Nonlinear and Neural Network-based Control of a Small Four-Rotor Aerial Robot," 2007 IEEE/ASME international conference on advanced intelligent mechatronics. DOI: 10.1109/AIM.2007.4412470 .
 Yan-Fei Teng, Bin Hu, Zhi-Wei Liu, Jian Huang, and Zhi-Hong Guan, "Adaptive Neural Network Control for Quadrotor Unmanned Aerial Vehicles," 2017 11th Asian Control Conference (ASCC) Gold Coast Convention Centre, Australia December 17-20.
 X Yu, Z Lv, Y Wu, XM Sun, "Neural network modeling and backstepping control for quadrotor," Chinese Automation Congress (CAC), 2018. DOI: 10.1109/CAC.2018.8623432 .
 C. Nicol1, C.J.B. Macnab, A. Ramirez-Serrano, "Robust Neural Network Control Of A Quadrotor Helicopter" Canadian Conference on Electrical and Computer Engineering, 2008. DOI: 10.1109/CCECE.2008.4564736 .
 S. Bansal; Anayo K. Akametalu; Frank J. Jiang; F. Laine; Claire J. Tomlin, “Learning Quadrotor Dynamics Using Neural Network for Flight Control,” IEEE 55th Conference on Decision and Control (CDC), 2016. DOI: 10.1109/CDC.2016.7798978 .
 Yan-Fei Teng, Bin Hu, Zhi-Wei Liu, Jian Huang, Zhi-Hong Guan, "Neural Network Adaptive Inverse Model Control Method for Quadrotor UAV," 35th Chinese Control Conference (CCC), 2016. DOI: 10.1109/ChiCC.2016.7553921 .
 Cai Luo, Zhenpeng Du, and Leijian Yu, "Neural Network Control Design for an Unmanned Aerial Vehicle with a Suspended Payload" Electronics 2019, 8, 931; doi:10.3390/electronics8090931 .
 Hadi Ramzi a, ∗, Sima Afshinfar, “Neural network-based adaptive sliding mode control design for position and attitude control of a quadrotor UAV” Aerospace Science and Technology Volume 91, August 2019, Pages 12-27 https://doi.org/10.1016/j.ast.2019.04.055 .
 Javier Gómez-Avila; Carlos López-Franco; Alma Y. Alanis; Nancy Arana-Daniel, “Control of Quadrotor using a Neural Network based PID”, IEEE Latin American Conference on Computational Intelligence (LA-CCI), 2018. DOI: 10.1109/LA-CCI.2018.8625222 .
 Xrumer Lin, Yulu Wang, Yunfei Liu, "Neural-network-based robust terminal sliding-mode control of quadrotor," Chinese Automatic Control Society and John Wiley & Sons Australia, 2020. https://doi.org/10.1002/asjc.2478 .
 Christopher Edmond Nicol, "A Robust Adaptive Neural Network Control for a Quadrotor Helicopter," Master thesis, University of Calgary, 2010.
 Osman Çakira*, Tolga Yüksel, "Neural Network Control for Quadrotors," American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS), (2017) Volume 31, No 1, pp 191-200.
 Qingzheng Xu · Zhisheng Wang · Ziyang Zhen, "Adaptive neural network finite-time control for quadrotor UAV with unknown input saturation," Nonlinear Dynamics volume 98, pages 1973–1998 (2019).
 Yan-min Chen, Yong-ling He & Min-Feng Zhou, "Decentralized PID neural network control for a quadrotor helicopter subjected to wind disturbance," Journal of Central South University volume 22, pages168–179 (2015).
 Hadi RAMZI, "Adaptive neural network-based sliding mode attitude control for a quadrotor UAV," Journal of Central South University volume 25, pages2654–2663 (2018).
 Travis Dierks, "Output Feedback Control of a Quadrotor UAV Using Neural Networks," IEEE Transactions on Neural Networks, Vol. 21, No. 1, January 2010.
 Weinan Gao, Jialu Fan1 and Yannong Li1, "Research on Neural Network PID Control Algorithm for a Quadrotor," Applied Mechanics and Materials Vols. 719-720 (2015) pp 346-351.
 Ts. Tengis; A. Batmunkh, "Experimental approach to Pole Placement problem of State Feedback Control for Quadrotor Stabilization in Hovering Mode," International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 6, Issue 9, September 2017.
 Ts. Tengis; A. Batmunkh, "State feedback control simulation of quadcopter model," 11th International Forum on Strategic Technology (IFOST), 2016. DOI: 10.1109/IFOST.2016.7884178 .