An Inverse Proportional Operator-Based D-Type Iterative Learning Control for Initial State Error

This paper studies the influence of incipient status deviation in iterative learning control(ILC) systems and comes up with a fresh D-type iterative learning control algorithm for i incipient status error. Then, it is shown that, when the proposed algorithm is the same with nonlinear systems, the effect of incipient status deviation is up to be cut down with the amount of iterations little by little and the proposed algorithm improves the convergence speed. Compared with traditional algorithms, the proposed algorithm is more flexible because of combining learning gain and correction function with the number of iterations. To demonstrate the availability of the posed arithmetic, a simulation experiment is provided.