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Model and experience‐based initial input construction for iterative learning control
Author(s) -
Freeman C. T.,
Alsubaie M. A.,
Cai Z.,
Rogers E.,
Lewin P. L.
Publication year - 2011
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.1209
Subject(s) - iterative learning control , trajectory , computer science , control theory (sociology) , tracking (education) , control signal , control (management) , control engineering , iterative method , robot , tracking error , artificial intelligence , engineering , algorithm , psychology , telecommunications , pedagogy , physics , astronomy , transmission (telecommunications)
The initial choice of input in iterative learning control (ILC) generally has a significant effect on the error incurred over subsequent trials. In this paper, techniques are developed that use experimental data gathered over previous applications of ILC in order to generate an initial input signal for the tracking of a new reference trajectory. A model‐based approach is then incorporated to overcome the limitation of insufficient previous experimental data, and a robust design procedure is developed. Experimental evaluation results are obtained using a gantry robot facility. Copyright © 2010 John Wiley & Sons, Ltd.