PERFORMANCE ANALYSIS OF ADVANCED CONTROL TECHNIQUES FOR FIXED-WING UNMANNED AERIAL VEHICLES

Abstract

Fixed-wing Unmanned Aerial Vehicles (UAVs) require robust lateral guidance and roll control strategies to achieve accurate trajectory tracking in autonomous navigation missions. This work presents a comparative evaluation of two inner-loop roll control approaches, Proportional-Integral-Derivative (PID) and an extended formulation of the classical Linear Quadratic Regulator (LQR), referred to as Extended LQR (ELQR). The method integrates roll rate penalization within the inner-loop of an L1-based lateral guidance controller, tailored for fixed-wing UAV lateral dynamics. A systematic comparison is conducted within a developed hybrid simulation framework that combines Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) configurations, enabling realistic modeling of flight dynamics and environmental disturbances. Controller performance is assessed using standardized time and control domain metrics. Results demonstrate that while the PID controller offers fast response and ease of implementation, ELQR produces smoother control action and lowers actuator demand without compromising tracking accuracy. These findings highlight the potential of ELQR as an effective alternative for fixed-wing UAV lateral control in dynamic and resource-constrained environments.