# Adaptive Visual Servoing Control for Hoisting Positioning Under Disturbance Condition
## 1 Introduction  
Automatic hoisting positioning technology is the main component of unmanned crane technology. The research into automatic hoisting positioning technology is conducive to the development of intelligent cranes and technology upgrading, which are key in the technology of cranes in the future. The key to improving the automation level of the hoisting operation is to realize accurate hoisting positioning (Figure 1). Port hoisting, prefabricated building construction and the installation of large energy and power equipment all need accurate hoisting positioning. The traditional positioning method is to install an absolute value encoder [1] on the driving shaft of the crane. The absolute value encoder converts the rotation of the shaft into the moving distance and transmits it to the control system, which judges whether the equipment arrives at a designated position. For conventional cranes, this design is feasible and widely used. However, when it is used in high-precision cranes, deviations occur. The reason is that the driving wheel slips, and the wheel shaft rotates but the crane does not move, resulting in the instability of the positioning system. In order to solve the problem of low positioning accuracy, the rack and pinion positioning system is introduced into the hoisting positioning technology. The rack and pinion positioning system [2] improves the positioning accuracy, and iswidely used in subsequent nuclear power projects. However, the rack and pinion positioning system (Figure 2) still faces many challenges: the rack needs to be laid out to its full length, and the machining accuracy of the rack itself is too high, which brings great trouble to the engineers. For a crane with long travel distances and precise positioning, researchers tried to use a cable encoder, which consists of a cable box and an absolute value encoder. As the cable is pulled out and retracted, the encoder measures the number of turns of the drum in the cable box and converts it into a measurement signal to output to the system. In the actual project, it is found that the cable is easily damaged in the installation and commissioning processes. Moreover, the magnetic ruler system [3] has been developed and applied to hoisting positioning, but it has not been popularized because of the limitations of the working environment. Radiofrequency technology [4] has also been used in this field, but its performance was greatly discounted due to signal shielding and interference.  
As a non-contact sensor, the camera can be used as the eye of the hoisting equipment to increase the ability of environmental perception. With this method, we can control the crane in a closed loop. In recent years, visual servoing has ben widely used in trajectory tracking and positioning technology [5,6]. However, in the hoisting and positioning operation, the external environment is unstable, and is easily affected by wind load, equipment vibration and other factors, which bring disturbances to the visual servo system, resulting in low accuracy of positioning, slow response speed and other problems. Therefore, in this paper, research into visual servo control under disturbance conditions is carried out.