Adaptive Neural Control Algorithm Design for Attitude Stabilization of Quadrotor UAV

Kheira Belhadri; Benatman Kouadri; Mohammed Lamine Zegai

doi:10.15866/ireaco.v9i6.9919

Adaptive Neural Control Algorithm Design for Attitude Stabilization of Quadrotor UAV

Kheira Belhadri^(1*), Benatman Kouadri⁽²⁾, Mohammed Lamine Zegai⁽³⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/ireaco.v9i6.9919

Abstract

This paper presents a new adaptive neural network control scheme to stabilize the attitude of the quadrotor helicopter. The dynamic model was developed via Newton−Euler formalism. The robust adaptive control is then realized using neural network (NN) algorithm based on a PID controller in the aim to adjust its gain parameters. The proposed algorithm is developed to adapt the structure of the conventional PID controller to a dynamic PID controller. Finally, the proposed controller is compared with that classical PID controller using MATLAB/Simulink. The simulation results show that the neural PID controller produces better performance than the conventional one, particularly in case of perturbation.
Copyright © 2016 Praise Worthy Prize - All rights reserved.

Keywords

Quadrotor Dynamic Model; Adaptive Control; PID Controller; Neural PID Controller; Attitude Control

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References

L. G Carrillo, E. Rondon, A. Sanchez, A Dzul, and R. Lozano, Stabilization and trajectory tracking of a quad-rotor using vision, Journal of Intelligent & Robotic Systems, vol. 61, no 1-4: 103-118 , 2011.
http://dx.doi.org/10.1007/s10846-010-9472-1

Bouabdellah, A. Noth and R. Siegwart, PID vs LQ control techniques applied to an indoor micro quadrotor, IEEE International Conference on Intelligent Robots and Systems, vol.3, pp.2451-2456, 2004.
http://dx.doi.org/10.1109/iros.2004.1389776

Deif, T., Kassem, A., El Baioumi, G., Modeling and Attitude Stabilization of Indoor Quad Rotor, (2014) International Review of Aerospace Engineering (IREASE), 7 (2), pp. 43-47.
http://dx.doi.org/10.15866/irease.v7i2.783

H. Bouadi, S. Simoes Cunha, A. Drouin, and F. Mora-Camino, Adaptive sliding mode control for quadrotor attitude stabilization and altitude tracking, Computational Intelligence and Informatics (CINTI),IEEE 12th International Symposium , Budapest, pp. 449-455, 2011.
http://dx.doi.org/10.1109/cinti.2011.6108547

S. Bouabdallah and R. Siegwart, Backstepping and sliding-mode techniques applied to an indoor micro quadrotor, IEEE International Conference on Robotics and Automation, pp.2247- 2252, Barcelona, Spain, April 2005.
http://dx.doi.org/10.1109/robot.2005.1570447

Z. Fang, and W. Gao, Adaptive integral backstepping control of a micro-quadrotor. In Intelligent Control and Information Processing (ICICIP), IEEE 2nd International Conference, vol. 2, pp. 910-915, July 2011.
http://dx.doi.org/10.1109/icicip.2011.6008382

Mohd Ariffanan Mohd Basri, Abdul Rashid Husain, Kumeresan A Danapalasingam, Stabilization and trajectory tracking control for underactuated quadrotor helicopter subject to wind-gust disturbance, Sadhana, August 2015, Volume 40, Issue 5, pp 1531–1553.
http://dx.doi.org/10.1007/s12046-015-0384-4

H. Voos, Nonlinear control of a quadrotor micro-UAV using feedback-linearization. In Mechatronics, ICM 2009. IEEE International Conference, pp. 1-6, 2009.
http://dx.doi.org/10.1109/icmech.2009.4957154

H. Desa , S. F. Ahmed, , A. Z. Azfar,Adaptive hybrid control algorithm design for attitude stabilization of quadrotor (UAV), Archives Des Sciences, vol 66, no. 2, pp. 51-64, 2013.
http://dx.doi.org/10.1109/icrom.2013.6510121

Deif, T., Kassem, A., El Baioumi, G., Modeling, Robustness, and Attitude Stabilization of Indoor Quad Rotor Using Fuzzy Logic Control, (2014) International Review of Aerospace Engineering (IREASE), 7 (6), pp. 192-201.
http://dx.doi.org/10.15866/irease.v7i6.4306

C. Cozaa, C. Nicola, C.J.B. Macnaba, and A. Ramirez-Serranob, Adaptive Fuzzy Control for a Quadrotor Helicopter Robust to Wind Buffeting, Journal of Intelligent & Fuzzy Systems, vol. 22, no 5, 6: 267-283, 2011.
http://dx.doi.org/10.1016/j.mechatronics.2011.02.007

D. Zhao, C. Sun, Q. Wang, and W. Yang, Neural network based PID control for quadrotor aircraft, In International Conference on Intelligent Science and Big Data Engineering, pp. 287-297. Springer International Publishing, 2015.
http://dx.doi.org/10.1007/978-3-319-23862-3_28

C. Yan-min, H. Yong-ling, Z. Min-feng, Decentralized PID Neural Network Control for a Quadrotor Helicopter Subjected to Wind Disturbance, Journal of Central South University, vol. 22:168-179, 2015.
http://dx.doi.org/10.1007/s11771-015-2507-9

C. Nicol , C. Macnab and A. Ramirez-Serrano, Robust neural network control of a quadrotor helicopter, IEEE Proceedings of the Canadian Conference on Electrical and Computer Engineering , pp. 1233-1238, 2008.
http://dx.doi.org/10.1109/ccece.2008.4564736

T. Dierks, and S. Jagannathan, Output Feedback Control of a Quadrotor UAV Using Neural Networks, IEEE Transactions on Neural Networks, vol. 21, no. 1, pp. 50-66, Jan 2010.
http://dx.doi.org/10.1109/tnn.2009.2034145

Elamine, L., Meguenni, K., Youssouf, M., Litim, M., Nonlinear Observer and Backstepping Control of Quadrotor Unmanned Aerial Vehicle, (2013) International Review of Automatic Control (IREACO), 6 (5), pp. 631-640.

A. Rubaai, M. J. Castro-Sitiriche and A. R. Ofoli, Design and Implementation of Parallel Fuzzy PID Controller for High-Performance Brushless Motor Drives: An Integrated Environment for Rapid Control Prototyping, IEEE Transactions on Industry Applications, vol. 44, no. 4, pp. 1090-1098, 2008.
http://dx.doi.org/10.1109/tia.2008.926059

M. L. Zegai, M. Bendjebbar ; K. Belhadri ; M. L. Doumbia ; B. Hamane ; P. M. Koumba, Direct torque control of induction motor based on artificial neural networks with estimate and regulation speed using the MRAS and neural PID controller, IEEE Electrical Power and Energy Conference (EPEC), pp. 320-325, 2015.
http://dx.doi.org/10.1109/epec.2015.7379970

S.Bouabdallah, Design and control of quadrotors with application to autonomous flying, Ph.D, EPFL, Lausanne, 2007.
http://dx.doi.org/10.1007/s10514-012-9279-y

Aziz, M., Elsayed, A., CFD Investigations for UAV and MAV Low Speed Airfoils Characteristics, (2015) International Review of Aerospace Engineering (IREASE), 8 (3), pp. 95-100.
http://dx.doi.org/10.15866/irease.v8i3.6212

Bousson, K., Gameiro, T., A Quintic Spline Approach to 4D Trajectory Generation for Unmanned Aerial Vehicles, (2015) International Review of Aerospace Engineering (IREASE), 8 (1), pp. 1-9.
http://dx.doi.org/10.15866/irease.v8i1.4780

Payam, A., Hassani, F., Fathipour, M., Design of Hybrid Closed Loop Control Systems for a MEMS Accelerometer Using Nonlinear Control Principles, (2014) International Review of Aerospace Engineering (IREASE), 7 (5), pp. 164-170.
http://dx.doi.org/10.15866/irease.v7i5.4972

Vikhram, G., Latha, S., Vikhram, G., Robust Shunt FACTS Controller Design for Power System Damping Improvement, (2013) International Review of Electrical Engineering (IREE), 8 (2), pp. 792-809.

Jin, Y., Lee, S., Kim, S., Yoon, Y., A Control Scheme for Price-Responsive Generations and Loads in support of Frequency Control within a Decentralized Environment, (2014) International Review of Electrical Engineering (IREE), 9 (3), pp. 527-537.

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