Control of non-linear Quadrotor using PID and Backstepping Techniques
How to Cite?
Ritika Thusoo, Sheilza Jain, Sakshi Bangia, "Control of non-linear Quadrotor using PID and Backstepping Techniques," International Journal of Engineering Trends and Technology, vol. 69, no. 7, pp. 167-173, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I7P223
Abstract
Quadrotorcan takeoff and land from any surface vertically. It has four rotors attached to each side of the arm and a processing unit attached to the center. The Quadrotor has rotational and translational movement. Rotational movements are known as roll, pitch, and yaw angles. The translational movements are along the x, y, and z planes. These movements are achieved by varying the voltages of the four rotors, which generate thrust and angular movement of the Quadrotor. In this paper, a mathematical model of Quadrotor is developed in MATLAB Simulink. Angle (Attitude) and Height (Altitude) of the Quadrotor are controlled using a PID controller. For position control, the Backstepping control technique is implemented. But to obtain a stable response for the motion along x and y, PID controller gains are tuned using a Particle Swarm Optimization (PSO) code. Similarly, the PID controller gain used in the subsystem that represents motion along the z-axis is tuned by cascading a PI controller with the subsystem. The paper is concluded with complete control of all six parameters of the Quadrotor system.
Keywords
Backstepping, PID, PSO, PI-PID Quadrotor.
Reference
[1] M. A. Boon, A. P. Drijfhout, and S. Tesfamichael., Comparison of a fixed-wing and multi-rotor UAV for environmental mapping applications: A case study, Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. - ISPRS Arch., 42(2W6) (2017) 47–54.
[2] M. Kamran Joyo, S. F. Ahmed, D. Hazry, M. H. Tanveer, and F. A. Warsi., Position Controller Design for Quad-rotor under Perturbed Condition, Wulfenia, 20(7) (2013) 178–189.
[3] L. Zhou, J. Zhang, H. She, and H. Jin., Quadrotor uav flight control via a novel saturation integral backstepping controller, Automatika, 60(2) (2019) 193–206.
[4] G. Sylvester., E-Agriculture in action: Drones for Agriculture, 53(9) (2018).
[5] S. Kedari, P. Lohagaonkar, M. Nimbokar, G. Palve, and P. P. Yevale., Real-Time Wireless Communication between Quadcopter and Android in Agriculture Field– A Review, Int. J. Adv. Res. Comput. Sci. Softw. Eng. Real-Time Wirel. Commun. Between Quadcopter Android Agric. F. – A Rev., 1 (2015) 706– 708.
[6] J. Kim, S. A. Gadsden, and S. A. Wilkerson., A Comprehensive Survey of Control Strategies for Autonomous Quadrotors, arXiv, 43(1) (2020) 3–16
[7] N. H. Motlagh, M. sBagaa, and T. Taleb., UAV-Based IoT Platform: A Crowd Surveillance Use Case, IEEE Commun. Mag., 55(2) (2017) 128–134.
[8] A. Intwala., A Review on Vertical Take-Off and Landing ( VTOL ) Vehicles, Innov. Res. Adv. Eng., 2(2) (2015) 186–191.
[9] D. J. Almakhles., Robust Backstepping Sliding Mode Control for a Quadrotor Trajectory Tracking Application, IEEE Access, 8 (2020) 5515–5525.
[10] W. Zhao, H. Liu, and F. L. Lewis., Data-Driven Fault-Tolerant Control for Attitude Synchronization of Nonlinear Quadrotors, IEEE Trans. Automat. Contr., 9286 (2021) 1–8.
[11] A. Shamshirgaran, D. Ebeigbe, and D. Simon., Position and Attitude Control of Underactuated Drones Using the Adaptive Function Approximation Technique, (2020).
[12] P. Salaskar, S. Paranjpe, J. Reddy, and A. Shah, Quadcopter – Obstacle Detection and Collision Avoidance., Int. J. Eng. Trends Technol., 17(2) (2014) 84–87.
[13] L. X. Xu, H. J. Ma, D. Guo, A. H. Xie, and D. L. Song., Backstepping Sliding-Mode and Cascade Active Disturbance Rejection Control for a Quadrotor UAV, IEEE/ASME Trans. Mechatronics, 25(6) (2020) 2743–2753.
[14] L. Zhou, J. Zhang, H. She, and H. Jin., Quadrotor uav flight control via a novel saturation integral backstepping controller, Automatika, 60(2) (2019) 193–206.
[15] A. Noordin, M. A. M. Basri, Z. Mohamed, and A. F. Z. Abidin., Modelling and PSO fine-tuned PID control of quadrotor UAV, Int. J. Adv. Sci. Eng. Inf. Technol., 7(4) (2017) 1367–1373.
[16] A. A. Mian and W. Daobo., Nonlinear flight control strategy for an underactuated quadrotor aerial robot, in Proceedings of IEEE International Conference on Networking, Sensing and Control, ICNSC, (2008) 938–942.
[17] R. Babaei and A. Farhad Ehyaei., Robust Backstepping Control of a Quadrotor UAV Using Extended Kalman Bucy Filter, 5(16) (2015) 2276–2291. Accessed: Apr. 30, 2019.
[18] Y. Yali, SunFeng, and W. Yuanxi., Controller Design of Quadrotor Aerial Robot, Phys. Procedia, 33 (2012)1254–1260.
[19] Tewari, Ashish., Advanced control of aircraft, spacecraft and rockets. John Wiley & Sons, (2011).
[20] K. A. Ghamry and Y. Zhang., Formation control of multiple quadrotors based on leader-follower method, in International Conference on Unmanned Aircraft Systems, ICUAS , (2015) 1037–1042.
[21] P. Wang, Z. Man, Z. Cao, J. Zheng, and Y. Zhao., Dynamics modelling and linear control of quadcopter, Int. Conf. Adv. Mechatron. Syst. ICAMechS, 0 (2016) 498–503.
[22] M. Hong, A. Bousbaine, M. H. Wu, and G. T. Poyi., Modelling and simulation of a quad-rotor helicopter, (2016).
[23] S. Musa., Techniques for Quadcopter Modelling & Design :A review,(2018).
[24] Q. Jiao, J. Liu, Y. Zhang, and W. Lian., Analysis and design the controller for quadrotors based on PID control method, in Proceedings - 33rd Youth Academic Annual Conference of Chinese Association of Automation, YAC, (2018) 88–92.
[25] Open PID Tuner for PID tuning - MATLAB. https://in.mathworks.com/help/slcontrol/ug/designingcontrollers- with-the-pid-tuner.html (accessed Oct. 07, 2019).
[26] I. a Raptis, K. P. Valavanis, and SpringerLink (Online service), Linear and Nonlinear Control of Small-Scale Unmanned Helicopters, (2011).
[27] D. Matouk, O. Gherouat, F. Abdessemed, and A. Hassam., Quadrotor position and attitude control via backstepping approach, Proc. 8th Int. Conf. Model. Identif. Control, ICMIC 2016, (2017)73–79.
[28] Z. Qi, Q. Shi, and H. Zhang., Tuning of digital PID controllers using particle swarm optimization algorithm for a CAN-Based DC motor subject to stochastic delays, IEEE Trans. Ind. Electron., 67(7) (2020) 5637–5646.
[29] Kiam Heong Ang, G. Chong, and Yun Li., PID control system analysis, design, and technology, IEEE Trans. Control Syst. Technol.,13(4) (2005) 559–576.