An adaptive composite anti-disturbance control for slung payload stabilization of an unmanned tandem helicopter

Aiming to address the problem of slung payload swing during trajectory tracking flight of an unmanned tandem helicopter in disturbed environments, an adaptive composite anti-disturbance control (ACADC) strategy is designed. The strategy is composed of active disturbance rejection control (ADRC) and adaptive radial basis function (RBF) neural network control, which is used for real-time estimation of the total disturbance, including disturbances caused by the suspended payload. A dynamic adjustment strategy driven by error has been proposed to adaptively tune the gain of the extended state observer (ESO). In the absence of a sensor capable of measuring the payload state, the RBF neural network is employed to approximate and compensate for hysteresis responses in the suspended payload. Furthermore, the stability of the proposed control strategy is analyzed using Lyapunov theory. Finally, the simulation verified the effectiveness and robustness of the adaptive control strategy under disturbance conditions. After applying the adaptive compensation strategy, the proposed control strategy effectively suppresses payload oscillation caused by disturbance and sudden trajectory changes while ensuring trajectory tracking accuracy.