The traditional crane automatic positioning method has low accuracy and poor stability

which can not form a real closed-loop control. The existing crane vision positioning methods generally have problems such as poor anti-interference performance

difficulty in convergence of vision error and difficulty in obtaining visual Jacobian matrix parameters. To solve the problem that the external disturbance affects the positioning accuracy and stability of visual servo system

this paper establishes the mathematical model of the position and attitude of the end effector under the disturbance condition

and proposes a visual servo disturbance suppressing method based on the Active Disturbance Rejection Controller. According to the characteristics of image projection

the relation between the parameters of Jacobian matrix and the differential of image feature is obtained

the adaptive updating rate of the parameters of Jacobian matrix is designed

and the closed-loop dynamic equation is established. According to the image feature error

the Lyapunov function is constructed and the system stability is proved. The simulation result shows that when the visual error converges

the position and velocity curves tend to zero. The method in this paper has satisfactory positioning accuracy in the case of visual uncertainty and external disturbance. It can ensure the positioning accuracy of the visual servo system and accelerate the convergence speed of the visual error under the disturbance condition. So

it is suitable for the control of the automatic positioning visual servo system of the hoisting crane.