Sliding Mode Controller Based on the Sliding Mode Observer for a QBall 2+ Quadcopter with Experimental Validation

(1) Ayoub Daadi Mail (Ecole Superieure Ali Chabati, Algeria)
(2) Houssam Boulebtinai Mail (Ecole Superieure Ali Chabati, Algeria)
(3) * Saddam Hocine Derrouaoui Mail (Ecole Superieure Ali Chabati Complex Systems Control and Simulators Laboratory, Ecole Militaire polytechnique, Algeria)
(4) Fares Boudjema Mail (Ecole Superieure Ali Chabati, Algeria)
*corresponding author


This paper studies a particular Unmanned Aerial Vehicle (UAV), called QBall 2+ quadcopter. This vehicle is a complex system, non-linear, strongly coupled, and under-actuated. First, a non-linear model was developed to represent the dynamics of the studied drone. Once the latter is established, the linear model was used to obtain the best gains of the Proportional Integral Derivative (PID) controller. This controller was applied after on the non-linear model of the UAV. Moreover, a Sliding Mode Controller (SMC) based on Sliding Mode Observer (SMO) was designed for retrieving the system unknown variables. Through these latter, the QBall 2+ was controlled, taking into account the observer errors. The first contribution in this work is to implement the PID regulator on the QBall 2+ flight controller to validate the results obtained by simulation. Secondly, due to the limitations of the Flex 3 cameras, especially when the drone is outside their working environment, the sliding mode observer was implemented to replace the cameras in order to measure the states of the system considered in this work. Simulation results of the different applied controllers were displayed to evaluate their effectiveness.


QBall 2+ quadcopter; PID controller; Sliding Mode Observer; Sliding Mode Control; Flight tests



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[1] I. Moad, M. Bouzid, M. Salami, and A. Fawaz, “A Review of Quadrotor Unmanned Aerial Vehicles: Applications, Architectural Design and Control Algorithms,” Journal of Intelligent & Robotic Systems, vol. 104, no. 2, pp. 1-33, 2022,

[2] S. H. Derrouaoui, Y. Bouzid, M. Guiani, and I. Dib, “A comprehensive review on reconfigurable drones: Classification, characteristics, design and control technologies,” Unmanned Systems, vol. 10, no. 01, pp. 3-29, 2022,

[3] S. H. Derrouaoui, Y. Bouzid, and M. Guiani, “PSO Based Optimal Gain Scheduling Backstepping Flight Controller Design for a Transformable Quadrotor,” Journal of Intelligent & Robotic Systems, vol. 102, no. 3, pp. 1-25, 2021,

[4] S. H. Derrouaoui, Y. Bouzid, and M. Guiani, “Towards a New Design with Generic Modeling and Adaptive Control of a Transformable Quadrotor,” The Aeronautical Journal, vol. 125, no. 1294, pp. 2169–2199, 2021,

[5] F. Munoz, N. S. ZUniga-Pena, L. R. G. Carrillo, E. S. Espinoza, S. Salazar, and M. A. Marquez, “Adaptive Fuzzy Consensus Control Strategy for UAS-Based Load Transportation Tasks,” IEEE Transactions on Aerospace and Electronic Systems, vol. 57, no. 6, pp. 3844-3860, 2021,

[6] L. Quan, L. Han, B. Zhou, S. Shen, and F. Gao, “Survey of UAV motion planning,” IET Cyber-systems and Robotics, vol. 1, no. 2, pp. 14-21, 2020,

[7] S. H. Derrouaoui, Y. Bouzid, and M. Guiani, “Adaptive integral backstepping control of a reconfigurable quadrotor with variable parameters’ estimation,” Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, pp. 09596518221087803, 2022,

[8] G. Nelson, M. Asaph, and K. Mercy, “A review of quad-rotor UAVs and their motion planning,” Proceedings of the Sustainable Research and Innovation Conference, pp. 117–121, 2022,

[9] Z. Zuo, “Trajectory tracking control design with command-filtered compensation for a quadrotor,” IET Control Theory and Application, vol. 4, pp. 2343-2355, 2009,

[10] I. Sa and P. Corke, “Vertical infrastructure inspection using a quadcopter and shared autonomy control,” Field and Service Robotics, vol. 92, pp. 219-232, 2014,

[11] K. Mathe and L. Busoniu, “Vision and control for UAVs: A survey of general methods and of inexpensive platforms for infrastructure inspection,” Sensors, vol. 15, no. 7, pp. 14887-14916, 2015,

[12] S. H. Derrouaoui, Y. Bouzid, and M. Guiani, “Nonlinear Robust Control of a New Reconfigurable Unmanned Aerial Vehicle,” Robotics, vol. 10, no. 2, p. 76, 2021,

[13] Quanser Innovate Educate, “Quanser Qball-2 user manual,” 2017,

[14] J. Ligthart, P. Poksawat, L. Wang, and H. Nijmeijer, “Experimentally validated model predictive control for a hexacopter,” IFAC PapersOnLine, vol. 50, pp. 4076-4081, 2017,

[15] R. Damen, M. Reyhanoglu, W. MacKunis, and J. R. Hervas, ”Passivity-based quaternion feedback control of a hover system,” 2016 16th International Conference on Control, Automation and Systems (ICCAS), 2016, pp. 201-206,

[16] M. Reyhanoglu and M. Rehan, “Nonlinear dynamics and control of aerial robots,” Chapter in Aerial Robots Aerodynamics, Control, and Applications, InTech, 2017, pp. 103-121,

[17] P. Yang, Z. Zhang, H. Geng, B. Jiang, and X. Hu, “Intelligent Discrete Sliding Mode Predictive FaultTolerant Control Method for Multi-Delay Quad-Rotor UAV System Based on DIECOA,” Aerospace, vol. 9, no. 4, p. 207, 2022,

[18] F. Chen, W. Lei, G. Tao, and B. Jiang, “Actuator fault estimation and reconfiguration control for the quadrotor helicopter,” International Journal of Advanced Robotic Systems, vol. 13, no. 1, p. 33, 2016,

[19] F. Pan, L. Liu, and D. Xue, “Optimal PID controller design with Kalman filter for Qball-X4 quad-rotor unmanned aerial vehicle,” Transactions of the Institute of Measurement and Control, vol. 39, no. 12, pp. 1785–1797, 2017,

[20] P. Lambert and M. Reyhanoglu, ”Observer-Based Sliding Mode Control of a 6-DOF Quadrotor UAV,” IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, 2018, pp. 2379-2384,

[21] M. Chen, S. Xiong, and Q. Wu, ”Tracking Flight Control of Quadrotor Based on Disturbance Observer,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 3, pp. 1414-1423, 2021,

[22] L. M. Elamine, K. Z. Meguenni, M. Youssouf, and L. Mustapha, ” Nonlinear observer, and PIbackstepping controller for unmanned aerial vehicle type quadrotor,” International Journal of Industrial Electronics and Drives, vol. 1, no. 4, 2014,

[23] J. Moreno-Valenzuela, R. Perez-Alcocer, M. Guerrero-Medina, and A. Dzul, ”Nonlinear PID-Type Controller for Quadrotor Trajectory Tracking,” IEEE/ASME Transactions on Mechatronics, vol. 23, no. 5, pp. 2436-2447, Oct. 2018,

[24] P. Yang, R. Guo, X. Pan, and T. Li, ”Study on the sliding mode fault tolerant predictive control based on multi agent particle swarm optimization,” Int. J. Control Autom. Syst., vol. 15, pp. 2034–2042, 2017,

[25] R. Perez-Alcocer and J. Moreno-Valenzuela, “A novel Lyapunov-based trajectory tracking controller for a quadrotor: Experimental analysis by using two motion tasks,” Mechatronics, vol. 61, pp. 58–68, 2019,

[26] Y. A. Younes, H. Noura, A. Rabhi, and A. E. Hajjaji, ”Actuator Fault-Diagnosis and Fault-Tolerant-Control using intelligent-Output-Estimator Applied on Quadrotor UAV,” 2019 International Conference on Unmanned Aircraft Systems (ICUAS), 2019, pp. 413-420,

[27] O. Kose and T. Oktay, “Dynamic Modeling and Simulation of Quadrotor for Different Flight Conditions,” European Journal of Science and Technology, vol. 15, pp. 132–142, 2019,

[28] B. Wang, X. Yu, L. Mu, and Y. Zhang, “A dual adaptive fault-tolerant control for a quadrotor helicopter against actuator faults and model uncertainties without overestimation,” Aerospace Science and Technology, p. 105744, 2020,

[29] K. Eliker, H. Bouadi, and M. Haddad, “Flight planning and guidance features for an uav flight management computer,” 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), 2016, pp. 1–6,

[30] S. Ullah, A. Mehmood, Q. Khan, S. Rehman, and J. Iqbal, ”Robust Integral Sliding Mode Control Design for Stability Enhancement of Under-actuated Quadcopter,” Int. J. Control Autom. Syst., vol. 18, pp. 1671–1678, 2020,

[31] M. Chen, S. Xiong, and Q.Wu, “Tracking flight control of quadrotor based on disturbance observer,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 3, pp. 1414-1432, 2021,

[32] S. John, ”Artificial Intelligent-Based Feedforward Optimized PID Wheel Slip Controller,” 2013 AFRICON, 2013, pp. 1-6,

[33] Y. Al Younes, H. Noura, M. Muflehi, A. Rabhi, and A. El Hajjaji, ”Model-free observer for state estimation applied to a quadrotor,” 2015 International Conference on Unmanned Aircraft Systems (ICUAS), 2015, pp. 1378-1384,

[34] M. H. Amoozgar, A. Chamseddine, and Y. Zhang, ”Experimental Test of a Two-Stage Kalman Filter for Actuator Fault Detection and Diagnosis of an Unmanned Quadrotor Helicopter,” J Intell Robot Syst, vol. 70, pp. 107–117, 2013,

[35] L. Chen, Z. Liu, H. Gao, and G. Wang, ”Robust adaptive recursive sliding mode attitude control for a quadrotor with unknown disturbances,” ISA transactions, vol. 122, pp. 114–125, 2022,

[36] A. Noordin, M. A. M. Basri, Z. Mohamed, and I. M. Lazim, ”Adaptive PID controller using sliding mode control approaches for quadrotor UAV attitude and position stabilization,” Arabian Journal for Science and Engineering, vol. 46, pp. 963-981, 2021,

[37] Y. Bouzid, S. H. Derrouaoui, and M. Guiatni,”PID Gain Scheduling for 3D Trajectory Tracking of a Quadrotor with Rotating and Extendable Arms,” 2021 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI), pp. 1-4, 2021,

[38] N. Fethalla, M. Saad, H. Michalska, and J. Ghommam, ”Robust observer-based dynamic sliding mode controller for a quadrotor UAV,” IEEE access, vol. 6, pp. 45846-45859, 2018,

[39] Z. Zhao, D. Cao, J. Yang, and H. Wang, ”High-order sliding mode observer-based trajectory tracking control for a quadrotor UAV with uncertain dynamics,” Nonlinear Dynamics, vol. 102, no. 4, pp. 2583-2596, 2020,

[40] W. Cai, J. She, M. Wu, and Y. Ohyama, ”Disturbance suppression for quadrotor UAV using sliding-mode-observer-based equivalent-input-disturbance approach,” ISA transactions, vol. 92, pp. 286–297, 2019,

[41] H. Castaneda, J. Rodriguez, and J. L. Gordillo, ”Continuous and smooth differentiator based on adaptive sliding mode control for a quad-rotor MAV,” Asian Journal of Control, vol. 23, pp. 661-672, 2021,

[42] Y. Rong, R. Jiao, S. Kang, and W. Chou, ”Sigmoid super-twisting extended state observer and sliding mode controller for quadrotor uav attitude system with unknown disturbance,” 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 2647-2653, 2019,

[43] S. H. Derrouaoui, Y. Bouzid, M. Guiani, K. Halfaoui, I. Dib and M. Moudjari, “Backstepping Controller Applied to a Foldable Quadrotor for 3D Trajectory Tracking,” ICINCO, pp. 537-544, 2020,

[44] S. H. Derrouaoui, Y. Bouzid, M. Guiani and A. Belmouhoub, “Trajectory Tracking of a Reconfigurable Multirotor Using Optimal Robust Sliding Mode Controller,” University of Eloued, 2022,


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Copyright (c) 2022 Ayoub Daadi, Houssam Boulebtinai, Saddam Hocine Derrouaoui, Fares Boudjema

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