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.
Existing Sparse Identification of Nonlinear Dynamics (SINDy)–based flight-control studies for fixed-wing aircraft have offered limited treatment of longitudinal–lateral coupling and explicit disturbance estimation, while nonlinear model predictive control remains highly sensitive to aerodynamic-model fidelity. This stu...
Min-Woo Kang, Jayden Dongwoo Lee, Seonghun Yun et al.· Journal of Aerospace Informa...· 0 citations
Numerical simulations demonstrate superior tracking accuracy and disturbance rejection capability compared to conventional adaptive neural DSC without disturbance observers, validating the effectiveness and robustness of the proposed scheme.
Xian Pan, Dong-Xue Wang, You-Wu Liu et al.· PLoS ONE· 0 citations
An optimal trajectory-tracking control method is developed for a two-degree-of-freedom (2-DOF) helicopter operating under uncertain dynamics and external disturbances, and an actor–critic learning structure is embedded into the controller design.
Zhi-Hui Liu, Yu-Lin Zhou· International Conference on...· 0 citations
In this study, we have developed a novel robust fixed-time control framework that integrates a fractional-order sliding mode control with a disturbance observer for a quadrotor UAV. The overall system dynamics are represented in a cascaded structure with two major loops: position and orientation (attitude). To facilita...
Nasser Firouzi, Younis K. Khdir· Journal of Vibration and Con...· 0 citations
This article investigates the attitude control problem of nonlinear uncrewed aerial vehicles subjected to uncertain internal parameters, unknown external disturbances, multiaxis coupling, and particularly time-varying input gains. A data-driven concurrent-learning (CL)-enhanced robust compensation control method (CL-Ro...
Zi-Jian Xiong, Yuan-Ming Xu, Xue-Tao Pian et al.· IEEE Transactions on Aerospa...· 0 citations
Quadrotor unmanned aerial vehicles (UAVs) are characterized by highly coupled, nonlinear, and underactuated dynamics, which make accurate trajectory tracking challenging in the presence of external disturbances, actuator faults, and model uncertainties. To address this problem, this paper designs a robust dual-loop tra...
Hao-Kun Wang, Ze-Hong Chen, Jin-Long Sun et al.· 2026 6th International Confe...· 0 citations
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