ESO-based fuzzy adaptive control of tiltrotor UAV against wind disturbance

Tiltrotor unmanned aerial vehicles (UAVs) face significant lateral control challenges during hovering due to their hybrid aerodynamic configuration, making them particularly susceptible to wind disturbances. This paper proposes a fuzzy adaptive control method integrating an extended state observer (ESO) with a multi-segment nonlinear state error feedback (NLSEF) function. The proposed approach introduces two key innovations: (1) a fuzzy logic-based ESO bandwidth adaptation mechanism that enhances disturbance estimation accuracy across varying wind conditions and (2) a multi-segment NLSEF controller that replaces the conventional two-segment design, refining the system’s response to different disturbances. Flight experiments conducted under no-wind, headwind, and crosswind conditions demonstrate that the proposed method reduces position error by 9.6%–61.5% compared to traditional approaches.