Active Anti-Disturbance Control Using Compensation Function Observer for QUAV Flight amidst Wind and Payloads

The flight of quadrotor unmanned aerial vehicles (QUAVs) faces challenges such as complex aerodynamic disturbances and time-varying payloads. To reject external disturbances and accommodate increased payloads, a control law based on a compensation function observer (CFO) and model compensation pole configuration control (CFO-based MCPCC) is proposed. The proposed control method incorporates error feedback, expected signal derivatives, disturbance estimation, and known model information, thereby achieving feedback linearization of the closed-loop system. The derivative of the reference signal is extracted using a high-order differentiator (HOD), which effectively filters out unwanted high-frequency components and improves the system’s control performance. Model deviations, payload variations, and external disturbances are estimated using the CFO, and the estimated values are compensated within the control law, thereby enhancing the system’s disturbance rejection capability. The utilization of known model information reduces the complexity of controller design. The proposed method is characterized not only as an active disturbance rejection control approach but also as a framework for compensating unknown dynamics. By employing Lyapunov stability theory, the asymptotic convergence of the integrated controller-observer system is demonstrated. To verify the effectiveness of the suggested control method in practice, experiments involving payload variations and wind disturbances are conducted. The results show that the proposed approach outperforms other methods in terms of payload and disturbance rejection capability. The results demonstrate that the proposed method ensures the system’s tracking control performance under payload variations and wind disturbances.