Learning observer-based sliding mode control for high-order helicopter with uncertainties and disturbances

Purpose This paper aims to propose a trajectory tracking control strategy for high-order helicopters under model uncertainties and unknown disturbances. Design/methodology/approach The control framework decomposes the system into two coupled subsystems: a position subsystem and a pitch angle subsystem. For each subsystem, an improved learning observer is designed to estimate external disturbances in real time. These estimates are integrated with sliding mode controllers to achieve precise altitude and pitch angle tracking. Findings The proposed method effectively addresses challenges posed by model uncertainties and disturbances, significantly enhancing disturbance estimation accuracy and compensation capabilities. Originality/value The closed-loop system’s stability is rigorously analyzed using Lyapunov stability theory. Numerical simulations validate the strategy’s effectiveness and robustness, demonstrating superior performance in handling high-order dynamics and multi-source disturbances compared to existing methods.