An L1 Adaptive Control Method with an Extended State Observer for Fixed-Wing UAV Attitude Control

To address issues such as nonlinear strong coupling, time-varying parameters, and external wind disturbances in fixed-wing unmanned aerial vehicles (UAVs) operating in complex flight environments, this study develops a composite attitude control method integrating L1 adaptive control with an extended state observer (ESO). First, pitch and roll attitude dynamic models considering nonlinear aerodynamic characteristics and channel coupling are established. Based on these models, a composite control architecture is developed in which the L1 adaptive controller establishes the baseline prediction-error-driven command-tracking loop and introduces matched-uncertainty compensation through a low-pass-filtered adaptive channel, whereas the ESO estimates a generalized extended state and, after removal of the known nominal drift term, provides an independently scaled auxiliary feedforward correction based on the resulting lumped-disturbance estimate. Although the uncertainty contents observed by the two mechanisms may partially overlap, their control actions are coordinated through the residual closed-loop disturbance and the prediction-error-driven adaptation process rather than being independently superimposed at full amplitude. Since the L1 adaptive law remains driven by the residual state-prediction error after the ESO action, the two mechanisms dynamically redistribute, rather than simply duplicate, the compensation effort. The control performance of the proportional–integral–derivative(PID) controller, the conventional L1 adaptive controller, and the proposed method is comparatively evaluated through simulations under typical operating conditions, including step response, sinusoidal tracking, composite wind disturbances, and measurement noise. The results show improved transient response and disturbance/noise rejection relative to PID and conventional L1 control under most of the tested conditions, while the high-frequency tracking benefit is channel-dependent. Overall, the proposed method improves transient response and disturbance/noise rejection while maintaining bounded tracking performance under the stated assumptions. The proposed method provides an effective approach for improving the attitude control performance of fixed-wing UAVs operating in complex environments.