Anti-disturbance attitude control for quadrotor unmanned aerial vehicle manipulator via fuzzy adaptive sigmoid generalized super-twisting sliding mode observer

During the flight of quadrotor unmanned aerial vehicle manipulator, external wind and model uncertainties will significantly affect the accuracy and stability of the controller. This study investigates the problem of high-precision attitude control for the quadrotor manipulator that is equipped with a 2-DOF robotic arm in presence of several disturbances based on a new sliding mode observer and a corresponding sliding mode controller. As for the proposed sliding mode observer, to reduce its estimation chattering phenomenon, a sigmoid function is exploited to replace the discontinuous signum function. Moreover, to adapt to the estimation of disturbances with different upper bounds of the first derivative, a fuzzy logic system algorithm is used to adaptively update the observer gains and slope parameters of the sigmoid function. Furthermore, a generalized super-twisting algorithm is incorporated into the proposed sliding mode observer. Similarly, the sliding mode controller is constructed by using the generalized super-twisting algorithm and a sigmoid function in addition to the sliding mode observer-based feedforward disturbance compensation. In addition, to further relieve the influence of system sensor noise, a tracking differentiator is exploited to incorporate with both proposed sliding mode observer and sliding mode controller. Finally, to demonstrate the effectiveness of the proposed method, several simulations and experiments on the quadrotor unmanned aerial vehicle manipulator system are conducted under varying external disturbances.