Trajectory tracking control by an adaptive iterative learning control with artificial neural networks

An iterative learning control(ILC) is a kind of the control algorithm which is capable of tracking a desired trajectory perfectly in a period. The conventional algorithm, however, have some drawbacks where some nominal parameters are required. In this paper, we propose to combine an adaptive control with artificial neural networks(ANNs) and an adaptive iterative learning control algorithm to overcome the problem. In the parameter updating of the ANNs, two cases where only the weights are updated and both the weights and the center of radial basis functions are updated are compared with respect to a performance. The efficiency of the proposed methods are examined by experiments of a golf-swing robot.