Model reference parametric adaptive iterative learning control
This data was imported from Scopus:
Authors: Yu, H., Deng, M., Yang, T.C. and Owens, D.H.
Journal: IFAC Proceedings Volumes (IFAC-PapersOnline)
Copyright © 2002 IFAC. Most of iterative learning control (ILC) methods requires that the relative degree of the plant is less than 2 for a linear system or the plant is passive for a non-linear system. A new model reference parametric adaptive iterative learning control using the command generator tracker (CGT) theory is proposed in this paper. The method can be applied to control a plant with a higher relative degree and it only requires to iteratively adjust nm + 2 parameters for an SISO plant. Therefore, the ILC control system is very simple. The proposed method is in the spirit of simple adaptive control which has received intensive researches during past two decades. Simulation results show the effectiveness and usefulness of the proposed method.