<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Linear Quadratic Regulator (LQR) is widely used in many practical engineering fields due to good stability margin and strong robustness. But there is little literature reports the technology that has been used to control the flying wing unmanned aerial vehicles (UAV). In this paper, aiming at the longitudinal static and dynamic characteristics of the flying wing UAV, LQR technology will be introduced to the flying wing UAV flight control. The longitudinal stability augmentation control law and longitudinal attitude control law are designed. The stability augmentation control law is designed by using output feedback linear quadratic method. It can not only increase the longitudinal static stability, but also improve the dynamic characteristics. The longitudinal attitude control law of the flying wing UAV is designed by using command tracking augmented LQR method. The controller can realize the control and maintain the flight attitude and velocity under the condition without breaking robustness of LQR. It solves the command tracking problems that conventional LQR beyond reach. Considering that some state variables of the system are difficult to obtain directly, a control method that called quasi-command tracking augmented LQR is designed by combing with the reduced order observer, it retains all the features of command tracking augmented LQR and more suitable for the application of practice engineering. Finally, the control laws are simulated under the environment of Matlab/Simulink. The results show that the longitudinal control laws of the flying wing UAV which are designed based on LQR can make the flying wing UAV achieve satisfactory longitudinal flying quality.</p></abstract>

Linear Quadratic Regulator (LQR) is widely used in many practical engineering fields due to good stability margin and strong robustness. But there is little literature reports the technology that has been used to control the flying wing unmanned aerial vehicles (UAV). In this paper, aiming at the longitudinal static and dynamic characteristics of the flying wing UAV, LQR technology will be introduced to the flying wing UAV flight control. The longitudinal stability augmentation control law and longitudinal attitude control law are designed. The stability augmentation control law is designed by using output feedback linear quadratic method. It can not only increase the longitudinal static stability, but also improve the dynamic characteristics. The longitudinal attitude control law of the flying wing UAV is designed by using command tracking augmented LQR method. The controller can realize the control and maintain the flight attitude and velocity under the condition without breaking robustness of LQR. It solves the command tracking problems that conventional LQR beyond reach. Considering that some state variables of the system are difficult to obtain directly, a control method that called quasi-command tracking augmented LQR is designed by combing with the reduced order observer, it retains all the features of command tracking augmented LQR and more suitable for the application of practice engineering. Finally, the control laws are simulated under the environment of Matlab/Simulink. The results show that the longitudinal control laws of the flying wing UAV which are designed based on LQR can make the flying wing UAV achieve satisfactory longitudinal flying quality.

Research on Longitudinal Control Algorithm for Flying Wing UAV Based on LQR Technology

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Linear Quadratic Regulator (LQR) is widely used in many practical engineering fields due to good stability margin and strong robustness. But there is little...

Research on Longitudinal Control Algorithm for Flying Wing UAV Based on LQR Technology

Publicado en línea: 16 dic 2013

Páginas: 2155 - 2181

Recibido: 30 jun 2013

Aceptado: 23 nov 2013

DOI: https://doi.org/10.21307/ijssis-2017-632

© 2013 Yibo Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.