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MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft
This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowled...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4477241/ https://www.ncbi.nlm.nih.gov/pubmed/26180839 http://dx.doi.org/10.1155/2015/247301 |
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author | Xu, Xieyu Yang, Lingyu Zhang, Jing |
author_facet | Xu, Xieyu Yang, Lingyu Zhang, Jing |
author_sort | Xu, Xieyu |
collection | PubMed |
description | This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all concerned damage conditions. An MRAC method is developed for the polytope model, of which the stability and asymptotic error convergence are theoretically proved. The proposed technique reduces the number of parameters to be adapted and thus decreases computational cost and requires less input information. The method is validated by simulations on NASA generic transport model (GTM) with damage. |
format | Online Article Text |
id | pubmed-4477241 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-44772412015-07-15 MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft Xu, Xieyu Yang, Lingyu Zhang, Jing ScientificWorldJournal Research Article This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all concerned damage conditions. An MRAC method is developed for the polytope model, of which the stability and asymptotic error convergence are theoretically proved. The proposed technique reduces the number of parameters to be adapted and thus decreases computational cost and requires less input information. The method is validated by simulations on NASA generic transport model (GTM) with damage. Hindawi Publishing Corporation 2015 2015-06-09 /pmc/articles/PMC4477241/ /pubmed/26180839 http://dx.doi.org/10.1155/2015/247301 Text en Copyright © 2015 Xieyu Xu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xu, Xieyu Yang, Lingyu Zhang, Jing MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft |
title | MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft |
title_full | MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft |
title_fullStr | MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft |
title_full_unstemmed | MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft |
title_short | MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft |
title_sort | mrac control with prior model knowledge for asymmetric damaged aircraft |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4477241/ https://www.ncbi.nlm.nih.gov/pubmed/26180839 http://dx.doi.org/10.1155/2015/247301 |
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