Advanced UAV system utilization of LQR and ESC techniques for flight control

Abstract

This paper aims to create an effective flight controller that can reject severe disturbances, improving accuracy and efficiency. Current UAV control research fails to reduce large external disturbances. Integrating Linear Quadratic Regulator and Extremum Seeking Control helps overcome these negative influences. This paper describes a novel controller that stabilizes UAV output responses and handles external disturbances. Linear Quadratic Regulator is used to stabilize and control the UAV under optimal flight conditions, whereas Extremum Seeking Control is utilized to counteract external disturbances. The recommended flight controller is compared to the Linear Quadratic Gaussian Regulator, which uses the Kalman Filter to reduce disturbances. This comparison analysis demonstrates our method's superiority. In addition, the UAV's pitch and yaw angles experience aggressive maneuver motions to test the controller. The proposed strategy reduces noise and harsh disturbances including step, ramp, and sinusoidal variables during agile maneuvers. This study defines disturbances as follows: External noise in control systems is random signal variations generated by external disturbance; Step disturbances are fast, long-lasting system signal changes; ramp disturbances are sluggish; and sinusoidal disturbances are periodic oscillations. These disturbances make system stability and functionality difficult. Since our control strategy reduces disturbances, the recommended method can adapt system output to random fluctuations, rapid changes, gradual changes, and periodic oscillations. Linear Quadratic Gaussian Regulator is able to reduce noise from the system's output, but it fails to produce satisfactory results during major disturbances. The proposed method, however, is unique since it develops a controller with advanced disturbance rejection capabilities.