Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0005-1098(02)00021-3
Title: On the P-type and Newton-type ILC schemes for dynamic systems with non-affine-in-input factors
Authors: Xu, J.-X. 
Tan, Y.
Keywords: Newton-type iterative learning control
P-type iterative learning control
Q-factor
Q-order
Issue Date: Jul-2002
Source: Xu, J.-X., Tan, Y. (2002-07). On the P-type and Newton-type ILC schemes for dynamic systems with non-affine-in-input factors. Automatica 38 (7) : 1237-1242. ScholarBank@NUS Repository. https://doi.org/10.1016/S0005-1098(02)00021-3
Abstract: In this paper, P-type learning scheme and Newton-type learning scheme are proposed for quite general nonlinear dynamic systems with non-affine-in-input factors. Using the contraction mapping method, it is shown that both schemes can achieve asymptotic convergence along learning repetition horizon. In order to quantify and evaluate the learning performance, new indices - Q-factor and Q-order - are introduced in particular to evaluate the learning convergence speed. It is shown that the P-type iterative learning scheme has a linear convergence order with limited learning convergence speed under system uncertainties. On the other hand, if more of system information such as the input Jacobian is available, Newton-type iterative learning scheme, which is originated from numerical analysis, can greatly speed up the learning convergence speed. The effectiveness of the two learning control methods are demonstrated through a switched reluctance motor system. © 2002 Elsevier Science Ltd. All rights reserved.
Source Title: Automatica
URI: http://scholarbank.nus.edu.sg/handle/10635/56903
ISSN: 00051098
DOI: 10.1016/S0005-1098(02)00021-3
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

37
checked on Dec 5, 2017

WEB OF SCIENCETM
Citations

29
checked on Dec 5, 2017

Page view(s)

28
checked on Dec 11, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.