Application of model-following adaptive neural network control theory in gust load alleviation

Rui Nie; Weiguo Zhang; Guangwen Li; Xiaoxiong Liu

doi:10.1109/ICAL.2009.5262891

Application of model-following adaptive neural network control theory in gust load alleviation

Rui Nie
, Weiguo Zhang
, Guangwen Li
, Xiaoxiong Liu

School of Automation

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Based on the model-following adaptive neural network control theory, a gust load alleviation controller for civil airplanes by direct force control is proposed. For Dryden power spectral density function, the rational spectral theory is used to set up the linear state-space model of the vertical gust. The effects of gust to aircraft are considered to develop the synthesized system model of aircraft and gust. Simulation results show that the gust load alleviation control system based on neural network control theory can obtain good robust stability and the capability of restraining gust turbulence and measurement noises can be obtained by using the method in this paper.

Original language	English
Title of host publication	Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009
Pages	389-393
Number of pages	5
DOIs	https://doi.org/10.1109/ICAL.2009.5262891
State	Published - 2009
Event	2009 IEEE International Conference on Automation and Logistics, ICAL 2009 - Shenyang, China Duration: 5 Aug 2009 → 7 Aug 2009

Publication series

Name	Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009

Conference

Conference	2009 IEEE International Conference on Automation and Logistics, ICAL 2009
Country/Territory	China
City	Shenyang
Period	5/08/09 → 7/08/09

Keywords

Direct force control
Gust load alleviation
Modeling and simulation
Neural network control

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10.1109/ICAL.2009.5262891

Cite this

Nie, R., Zhang, W., Li, G., & Liu, X. (2009). Application of model-following adaptive neural network control theory in gust load alleviation. In Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009 (pp. 389-393). Article 5262891 (Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009). https://doi.org/10.1109/ICAL.2009.5262891

@inproceedings{a402254580db4d6bbe07998f4285f89b,

title = "Application of model-following adaptive neural network control theory in gust load alleviation",

abstract = "Based on the model-following adaptive neural network control theory, a gust load alleviation controller for civil airplanes by direct force control is proposed. For Dryden power spectral density function, the rational spectral theory is used to set up the linear state-space model of the vertical gust. The effects of gust to aircraft are considered to develop the synthesized system model of aircraft and gust. Simulation results show that the gust load alleviation control system based on neural network control theory can obtain good robust stability and the capability of restraining gust turbulence and measurement noises can be obtained by using the method in this paper.",

keywords = "Direct force control, Gust load alleviation, Modeling and simulation, Neural network control",

author = "Rui Nie and Weiguo Zhang and Guangwen Li and Xiaoxiong Liu",

year = "2009",

doi = "10.1109/ICAL.2009.5262891",

language = "英语",

isbn = "9781424447954",

series = "Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009",

pages = "389--393",

booktitle = "Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009",

note = "2009 IEEE International Conference on Automation and Logistics, ICAL 2009 ; Conference date: 05-08-2009 Through 07-08-2009",

}

Nie, R, Zhang, W, Li, G & Liu, X 2009, Application of model-following adaptive neural network control theory in gust load alleviation. in Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009., 5262891, Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009, pp. 389-393, 2009 IEEE International Conference on Automation and Logistics, ICAL 2009, Shenyang, China, 5/08/09. https://doi.org/10.1109/ICAL.2009.5262891

Application of model-following adaptive neural network control theory in gust load alleviation. / Nie, Rui; Zhang, Weiguo; Li, Guangwen et al.
Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009. 2009. p. 389-393 5262891 (Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Application of model-following adaptive neural network control theory in gust load alleviation

AU - Nie, Rui

AU - Zhang, Weiguo

AU - Li, Guangwen

AU - Liu, Xiaoxiong

PY - 2009

Y1 - 2009

N2 - Based on the model-following adaptive neural network control theory, a gust load alleviation controller for civil airplanes by direct force control is proposed. For Dryden power spectral density function, the rational spectral theory is used to set up the linear state-space model of the vertical gust. The effects of gust to aircraft are considered to develop the synthesized system model of aircraft and gust. Simulation results show that the gust load alleviation control system based on neural network control theory can obtain good robust stability and the capability of restraining gust turbulence and measurement noises can be obtained by using the method in this paper.

AB - Based on the model-following adaptive neural network control theory, a gust load alleviation controller for civil airplanes by direct force control is proposed. For Dryden power spectral density function, the rational spectral theory is used to set up the linear state-space model of the vertical gust. The effects of gust to aircraft are considered to develop the synthesized system model of aircraft and gust. Simulation results show that the gust load alleviation control system based on neural network control theory can obtain good robust stability and the capability of restraining gust turbulence and measurement noises can be obtained by using the method in this paper.

KW - Direct force control

KW - Gust load alleviation

KW - Modeling and simulation

KW - Neural network control

UR - https://www.scopus.com/pages/publications/70450205607

U2 - 10.1109/ICAL.2009.5262891

DO - 10.1109/ICAL.2009.5262891

M3 - 会议稿件

AN - SCOPUS:70450205607

SN - 9781424447954

T3 - Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009

SP - 389

EP - 393

BT - Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009

T2 - 2009 IEEE International Conference on Automation and Logistics, ICAL 2009

Y2 - 5 August 2009 through 7 August 2009

ER -

Nie R, Zhang W, Li G, Liu X. Application of model-following adaptive neural network control theory in gust load alleviation. In Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009. 2009. p. 389-393. 5262891. (Proceedings of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009). doi: 10.1109/ICAL.2009.5262891

Application of model-following adaptive neural network control theory in gust load alleviation

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