Towards High-Precision Quadrotor Trajectory Following Capabilities: Modelling, Parameter Estimation, and LQR Control

被引:2
作者
Hanif, A. [1 ]
Putro, I. E. [1 ]
Riyadl, A. [1 ]
Sudiana, O. [1 ]
Irwanto, H. Y. [1 ]
机构
[1] Natl Res & Innovat Agcy BRIN, Res Org Aeronaut & Space, Jakarta 10340, Indonesia
关键词
Control; LQR; modelling; parameter estimation; quadrotor; unmanned aerial vehicles (UAVs);
D O I
10.2478/lpts-2024-0015
中图分类号
O59 [应用物理学];
学科分类号
摘要
Quadrotor unmanned aerial vehicles (UAVs) are small, agile four-rotor systems suitable for various applications, from surveillance to disaster support missions. Hence, achieving high-precision trajectory tracking is crucial for their successful deployment. This research focuses on modelling, parameter identification, and Linear Quadratic Regulator (LQR) control design for quadrotors, aiming to enhance their trajectory following capabilities. The quadrotor dynamics are a sixth degree-of-freedom (6DOF) equation of motion derived from Newton's second law, encompassing moment of inertia, centre of gravity, weight, and thrust of propeller parameters. Experimental measurements are conducted to accurately determine these parameters, ensuring a realistic representation of the quadrotor system. Subsequently, a linearized model is constructed to provide a suitable plant for control system development. The LQR control design is intended to improve the trajectory tracking performance. This control strategy is validated through simulation and practical experiments, demonstrating its effectiveness in achieving high-precision trajectory following capabilites. The proposed approach demonstrates that LQR control effectively guides the quadrotor to resemble a predefined trajectory, experiencing only 3 % overshoot observed during the initial phase of flight.
引用
收藏
页码:89 / 104
页数:16
相关论文
共 17 条
[1]   Generalization of parallel axis theorem for rotational inertia [J].
Abdulghany, A. R. .
AMERICAN JOURNAL OF PHYSICS, 2017, 85 (10) :791-795
[2]   Towards autonomous indoor micro VTOL [J].
Bouabdallah, S ;
Murrieri, P ;
Siegwart, R .
AUTONOMOUS ROBOTS, 2005, 18 (02) :171-183
[3]   Optimal tracking controller design for a small scale helicopter [J].
Budiyono, Agus ;
Wibowo, Singgih S. .
JOURNAL OF BIONIC ENGINEERING, 2007, 4 (04) :271-280
[4]  
Erdelj M, 2017, IEEE PERVAS COMPUT, V16, P24, DOI 10.1109/MPRV.2017.11
[5]   MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory [J].
Guardeno, Rafael ;
Lopez, Manuel J. ;
Sanchez, Victor M. .
ROBOTICS, 2019, 8 (02)
[6]  
Islam M, 2019, 2019 7TH INTERNATIONAL CONFERENCE ON MECHATRONICS ENGINEERING (ICOM), P1, DOI [10.1109/icom47790.2019.8952046, 10.1109/3ict.2019.8910301]
[7]  
Kabir A. M.., 2019, arXiv
[8]   LQR controller design for quad-rotor helicopters [J].
Okyere, Emmanuel ;
Bousbaine, Amar ;
Poyi, Gwangtim T. ;
Joseph, Ajay K. ;
Andrade, Jose M. .
JOURNAL OF ENGINEERING-JOE, 2019, (17) :4003-4007
[9]  
Padfield G. D., 2007, Helicopter FlightDynamics: The Theory and Application ofFlying Qualities and Simulation Modelling, V2nd
[10]  
Priyambodo T. K., 2019, J. Telecommun. Electron. Comput.Eng. (JTEC)., V12, P2289