Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance
This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis a...
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Hindawi Limited
2017-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2017/1401427 |
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doaj-4692f0ac476145c0ab3544112e28783c2020-11-24T20:40:36ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472017-01-01201710.1155/2017/14014271401427Robust Adaptive Neural Control of Morphing Aircraft with Prescribed PerformanceZhonghua Wu0Jingchao Lu1Jingping Shi2Yang Liu3Qing Zhou4School of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaXi’an Aeronautics Computing Technique Research Institute, AVIC, Xi’an 710068, ChinaThis study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) technique, prescribed performance control, and a kind of smooth switching strategy into back-stepping design, a new composite switching adaptive neural prescribed performance control scheme is proposed and a new type of adaptive laws is constructed for the altitude subsystem. Compared with previous neural control scheme for flight vehicle, the remarkable feature is that the proposed controller not only achieves the prescribed performance including transient and steady property but also addresses the constraint on NN. Two comparative simulations are presented to verify the effectiveness of the proposed controller.http://dx.doi.org/10.1155/2017/1401427 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhonghua Wu Jingchao Lu Jingping Shi Yang Liu Qing Zhou |
spellingShingle |
Zhonghua Wu Jingchao Lu Jingping Shi Yang Liu Qing Zhou Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance Mathematical Problems in Engineering |
author_facet |
Zhonghua Wu Jingchao Lu Jingping Shi Yang Liu Qing Zhou |
author_sort |
Zhonghua Wu |
title |
Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance |
title_short |
Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance |
title_full |
Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance |
title_fullStr |
Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance |
title_full_unstemmed |
Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance |
title_sort |
robust adaptive neural control of morphing aircraft with prescribed performance |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2017-01-01 |
description |
This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) technique, prescribed performance control, and a kind of smooth switching strategy into back-stepping design, a new composite switching adaptive neural prescribed performance control scheme is proposed and a new type of adaptive laws is constructed for the altitude subsystem. Compared with previous neural control scheme for flight vehicle, the remarkable feature is that the proposed controller not only achieves the prescribed performance including transient and steady property but also addresses the constraint on NN. Two comparative simulations are presented to verify the effectiveness of the proposed controller. |
url |
http://dx.doi.org/10.1155/2017/1401427 |
work_keys_str_mv |
AT zhonghuawu robustadaptiveneuralcontrolofmorphingaircraftwithprescribedperformance AT jingchaolu robustadaptiveneuralcontrolofmorphingaircraftwithprescribedperformance AT jingpingshi robustadaptiveneuralcontrolofmorphingaircraftwithprescribedperformance AT yangliu robustadaptiveneuralcontrolofmorphingaircraftwithprescribedperformance AT qingzhou robustadaptiveneuralcontrolofmorphingaircraftwithprescribedperformance |
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1716826319685156864 |