Iterative reference adjustment for high precision and repetitive motion control applications

In this paper, a new iterative learning control (ILC) scheme is proposed which is suitable for high precision and repetitive motion control applications. Unlike the usual ILC scheme which adapts a feedforward control signal to achieve improved tracking performance over time, the proposed scheme iteratively adjusts the reference signal. To achieve a higher convergence rate, a radial basis function neural network is employed to model the tracking...