TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES
Online ISSN : 2189-4205
Print ISSN : 0549-3811
ISSN-L : 0549-3811
Multi-Variable Iterative Learning Identification and Its Application to Estimation of Aerodynamic Derivatives in an Aircraft Model
Atsushi FUJIMORIShinsuke OHARA
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JOURNAL OPEN ACCESS

2012 Volume 55 Issue 2 Pages 123-132

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Abstract
This paper presents a system identification technique, called iterative learning identification for multi-variable continuous-time state-space (SS) systems using iterative learning control. The transfer function (TF) parameters are regarded as functions with respect to the SS parameters that are to be identified. The relationship between the SS parameters and the response error is explicitly derived. An updated law of the SS parameters is given so as to reduce the response error. The proposed technique is applied to estimation of aerodynamic derivatives in a lateral linear model of aircraft. The effectiveness is demonstrated in numerical simulations.
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© 2012 The Japan Society for Aeronautical and Space Sciences
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