Design and implementation of visual predictive control for image positioning of an automatic alignment stage

The image positioning of an automatic alignment stage typically contains two important steps: image processing to identify the current coordinates of used markers and servo motion control to minimize the tracking errors in position or image coordinate. This paper investigates the practical use and performance of model predictive control (MPC) in image positioning of a XYθ motor stage system for peg and hole alignment applications. MPC has the advantages of calculating the optimal control moves based on a predicted model while considering the system constraints in the control design at the same time. The image update rate of the alignment system is set as 5 Hz and the stage servo rate for MPC is chosen as 100 Hz. The pose difference between the targeted and stage features is applied as the set point reference for MPC control system. The image tracking experiments demonstrate the effectiveness of the proposed MPC approach.