Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCA.2009.5410155
Title: On iterative learning control with high-order internal models
Authors: Liu, C.
Xu, J. 
Wu, J.
Tan, Y.
Issue Date: 2009
Source: Liu, C., Xu, J., Wu, J., Tan, Y. (2009). On iterative learning control with high-order internal models. 2009 IEEE International Conference on Control and Automation, ICCA 2009 : 1565-1570. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCA.2009.5410155
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-type ILC, and possible extension to nonlinear cases are also explored in this work. ©2009 IEEE.
Source Title: 2009 IEEE International Conference on Control and Automation, ICCA 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/71208
ISBN: 9781424447060
DOI: 10.1109/ICCA.2009.5410155
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