Robust Intelligent Attitude Control of Fixed-Wing UAVs Under Wind Disturbances
Year: 2026
Type: conference-paper
Abstract: Achieving robust attitude control for fixed-wing Unmanned Aerial Vehicles (UAVs) remains challenging due to nonlinear aerodynamics, strong coupling between motion axes, and sensitivity to wind disturbances. This research presents a comprehensive comparative evaluation of three control strategies. Incremental Nonlinear Dynamic Inversion (INDI), Sliding Mode Control (SMC) and an Artificial Neural Network (ANN) based controller are designed for roll and pitch attitude tracking of a fixed-wing UAV. To address the practical limitation that angular accelerations are not directly measurable in UAV systems, a Kalman filter is incorporated into the INDI framework to estimate angular acceleration signals required for incremental control implementation. The controllers are examined under nominal conditions and under severe conditions of wind disturbances. Simulation results show the INDI controller achieves the most balanced performance by maintaining accurate attitude tracking with low steady-state error, smooth transient response and significantly reduced actuator demand across all wind scenarios. The ANN controller performs adequately only under nominal conditions and exhibits degraded behavior under cross and reverse windy environments. The findings demonstrate that nonlinear control techniques offer superior robustness compared to data-driven intelligent methods in safety-critical and highly disturbed flight conditions.
Institution: Military Technical College
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7169782863