Iterative Learning Control for Accelerated Inhibition Effect of Initial State Error

An iterative learning control (ILC) with accelerated initial state correction is proposed for linear time-invariant systems with initial state deviations to improve tracking performance. Correction interval, which fallen sharply with the increasing of the iterations number, is designed for con- trolled object with any arbitrary initial state. In the correction interval, the initial state error is corrected by using the control algorithm, however in the outside of the interval, the control algorithm is same as the one without initial state error and realize zero error tracking of reference signal. The convergence of the proposed algorithm is proved in a paradigmatic sense. The designed ILC control method for LTI has better tracking performance by compared with the classical ILC control without initial state error. The numerical simulation verifies the effectiveness of the algorithm.