Design and Stability Analysis of an Aerosonde UAV Using Linear Quadratic Regulator Control

Abstract

Unmanned Aerial Vehicles (UAVs) have become increasingly important in surveillance, environmental monitoring, mapping, and scientific research, where flight stability and control performance are essential for safe and reliable operation. This study focuses on the modeling and stability analysis of an Aerosonde UAV using a Linear Quadratic Regulator (LQR) control approach. The main objective is to develop an optimal state-feedback controller capable of improving the stability and dynamic response of the UAV. A mathematical model of the Aerosonde UAV is established using longitudinal and lateral-directional flight dynamics and represented in state-space form. The LQR controller is designed by minimizing a quadratic performance index that balances state regulation and control effort through appropriate weighting matrices. The resulting feedback gains are applied to the longitudinal and lateral dynamic models, and numerical simulations are performed to compare the uncontrolled and LQR-controlled responses. The simulation results show that the LQR controller significantly improves the dynamic behavior of the UAV by reducing oscillations, decreasing overshoot, and accelerating convergence toward the equilibrium conditions. In the longitudinal dynamics, the controlled responses of velocity, vertical motion, pitch rate, altitude, and pitch angle exhibit improved stability compared with the uncontrolled system. Similarly, the lateral-directional responses demonstrate improved damping and faster convergence for lateral velocity, roll rate, yaw rate, roll angle, and yaw angle. These results confirm that the proposed LQR approach provides an effective state-feedback control strategy for improving the stability and dynamic performance of the Aerosonde UAV. The study provides a foundation for future investigations involving robust, adaptive, or intelligent control techniques under external disturbances and model uncertainties.