Experimental verification of the stability analysis of learning feed-forward control

In this paper the learning feedforward control (LFFC) scheme is considered. This type of controller is used for processes that repeatedly perform a specific task. LFFC compensates both for reproducible disturbances that depend on the state of the process, and for remaining random disturbances. The random disturbances are compensated by a feedback controller. The reproducible disturbances are compensated by a learning component consisting of a B-spline neural network that is operated in feedforward. In previous research, the stability properties LFFC were analyzed. From this analysis, quantitative criteria were obtained for selection of the support of the B-splines, and of the learning rate, for which the system is guaranteed to be stable. In this research the validity of the criteria is verified by means of experiments on a linear motor motion system.