Conference Proceedings

On Iterative Learning Control with High-Order Internal Models

Chunping Liu, Jianxin Xu, Jun Wu, Ying Tan

2009 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-3 | IEEE | Published : 2009

Abstract

In this work we focus on iterative learning control (ILC) for iteratively varying reference trajectories which are described by a high-order internal models (HOIM) that can be formulated as a polynomials between two consecutive iterations. The classical ILC with iteratively invariant reference trajectories, on the other hand, is a special case of HOIM where the polynomial renders to a first-order internal model with a unity coefficient. By incorporating HOIM into the ILC law, and designing appropriate learning control gains, the learning convergence in the iteration axis can be guaranteed for continuous-time linear time-varying (LTV) systems. The initial resetting condition, P-type and D-typ..

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University of Melbourne Researchers

Grants

Awarded by National Natural Science Foundation of China


Awarded by 973 Program of China


Awarded by 863 program of China


Awarded by 11 Project of China


Funding Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grants No.60774001,No.60736021 and No.60721062),the 973 Program of China(Gran No.2009CB320603),the 863 program of China(Grant No.2008AA042602),the 111 Project of China(Grant No.B07031) and the Qian Jiang expert program of Hangzhou