In this study, the probability density function (PDF) control method has been developed to deal with the random tracking
error for a class of robotic manipulator that are subjected to non-Gaussian noises. The control aim is that the shape of the
PDF of the tracking error is made as close as possible to the desired PDF. The ILC frame about PDF control approach of
manipulators system with non-Gaussian noises has been proposed and a recursive optimization solution batch-by-batch
has been developed. In each batch, nonlinear closed-loop error dynamics is considered. In addition, the convergence
condition of the tracking control algorithm has been analyzed. Finally, a simulation is given to illustrate the efficiency of
the proposed approach.