A fuzzy self-tuning algorithm for depth-axis control in image-based visual servo control

This paper is concerned with choosing image features for image-based visual servo control and how a fuzzy self-tuning PI control algorithm is designed to track a planar target with motion along the depth-axis. In this paper, we study a specific class of IBVS problem, in which a camera is constrained to move in the depth-axis(or Z-axis), since depth control is very important in IBVS system. Such a constraint condition makes it possible to find image moments reflecting target depth, and thus leads to a relative simple PI depth controller. The fizzy self tuning algorithm is introduced to improve the performance of the PI depth controller And the significant properties of the simulation results show that the fuzzy self tuning algorithm is shown by simulation.