Iterative learning control for position tracking of a pneumatic actuated X-Y table

The iterative learning control (ILC) learns the unknown information from repeated control operations. The tracking error from previous stages is used as the correction factor for the next control action. Therefore, the ILC controller can make the system tracking error converge to a small region within the limited numbers of iterations. A proportional-valve controlled pneumatic X-Y table system is built to perform the position tracking control experiments. The ILC controllers are implemented in the experiments and the results are compared. The P-type updating law with delay parameters are used for both the x and y axes in the repetitive trajectory tracking control. Experimental results show that the ILC controller can effectively control the system to track the given circular trajectory at different speeds. The controller parameters are varied for studying their effects. Inertial disturbance is also added to show the learning performance of the ILC controller.