Please use this identifier to cite or link to this item: https://doi.org/10.1109/TIE.2010.2070774
Title: Iterative learning control for sampled-data systems: From theory to practice
Authors: Abidi, K.
Xu, J.-X. 
Keywords: Iterative learning control (ILC)
precision control
sampled-data systems
Issue Date: Jul-2011
Source: Abidi, K., Xu, J.-X. (2011-07). Iterative learning control for sampled-data systems: From theory to practice. IEEE Transactions on Industrial Electronics 58 (7) : 3002-3015. ScholarBank@NUS Repository. https://doi.org/10.1109/TIE.2010.2070774
Abstract: This paper aims to present a framework for the design and performance analysis of iterative learning control (ILC) for sampled-data systems. The analysis is presented in both time and frequency domains. Monotonic convergence criteria are derived in both time and frequency domains and coined in ILC designs. In particular, the causes or conditions that lead to the poor transient responses in the time domain are explored and disclosed. Four ILC designs associated with different learning functions and filters are considered, namely, the P-type, D-type, D2-type, and general filters. The criteria for the selection of each type are presented. In addition, a relationship is shown between sampling-time selection and ILC convergence. Theoretical work concludes with a guideline for the ILC designs. Simulation results are shown to support the theoretical analysis in the time and frequency domains. Furthermore, based on the frequency-domain design tools, a successful experimental implementation on an electric piezomotor is demonstrated. © 2006 IEEE.
Source Title: IEEE Transactions on Industrial Electronics
URI: http://scholarbank.nus.edu.sg/handle/10635/82589
ISSN: 02780046
DOI: 10.1109/TIE.2010.2070774
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