Control of reusable launch vehicle using neuro-adaptive approach

Yong D. SONG; Xiao H. LIAO; M. D. GHEORGHIU; Ran ZHANG; Yao LI

doi:10.1007/11427469_30

Control of reusable launch vehicle using neuro-adaptive approach

Yong D. SONG^*
, Xiao H. LIAO
, M. D. GHEORGHIU
, Ran ZHANG
, Yao LI

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

1 Citation (Scopus)

Abstract

This work explores neural networks (NN) based control approach to nonlinear flight systems in the presence of disturbances and uncertainties. Neuro-adaptive control incorporating with two neural network (NN) units is proposed to cope with NN reconstruction error and other lumped system uncertainties. It is shown that with the proposed strategy, the angles of attack, sideslip and body-axis roll of the vehicle are effectively controlled. The method does not involve analytical estimation of the upper bounds on ideal weights, reconstruction error, or nonlinear functions. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Analyses and simulations confirm the effectiveness of the proposed control scheme. © Springer-Verlag Berlin Heidelberg 2005.

Original language	English
Title of host publication	Advances in Neural Networks: ISNN 2005: Second International Symposium on Neural Networks. Proceedings
Editors	Jun WANG, Xiao-Feng LIAO, Zhang YI
Publisher	Springer Berlin Heidelberg
Pages	192-197
Number of pages	6
ISBN (Electronic)	9783540320692
ISBN (Print)	9783540259145
DOIs	https://doi.org/10.1007/11427469_30
Publication status	Published - 2005
Externally published	Yes

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@inproceedings{4c4f715bb0b24648ae23364588f09fc5,

title = "Control of reusable launch vehicle using neuro-adaptive approach",

abstract = "This work explores neural networks (NN) based control approach to nonlinear flight systems in the presence of disturbances and uncertainties. Neuro-adaptive control incorporating with two neural network (NN) units is proposed to cope with NN reconstruction error and other lumped system uncertainties. It is shown that with the proposed strategy, the angles of attack, sideslip and body-axis roll of the vehicle are effectively controlled. The method does not involve analytical estimation of the upper bounds on ideal weights, reconstruction error, or nonlinear functions. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Analyses and simulations confirm the effectiveness of the proposed control scheme. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.",

author = "SONG, \{Yong D.\} and LIAO, \{Xiao H.\} and GHEORGHIU, \{M. D.\} and Ran ZHANG and Yao LI",

year = "2005",

doi = "10.1007/11427469\_30",

language = "English",

isbn = "9783540259145",

pages = "192--197",

editor = "Jun WANG and Xiao-Feng LIAO and Zhang YI",

booktitle = "Advances in Neural Networks: ISNN 2005: Second International Symposium on Neural Networks. Proceedings",

publisher = "Springer Berlin Heidelberg",

}

Control of reusable launch vehicle using neuro-adaptive approach. / SONG, Yong D.; LIAO, Xiao H.; GHEORGHIU, M. D. et al.
Advances in Neural Networks: ISNN 2005: Second International Symposium on Neural Networks. Proceedings. ed. / Jun WANG; Xiao-Feng LIAO; Zhang YI. Springer Berlin Heidelberg, 2005. p. 192-197.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - Control of reusable launch vehicle using neuro-adaptive approach

AU - SONG, Yong D.

AU - LIAO, Xiao H.

AU - GHEORGHIU, M. D.

AU - ZHANG, Ran

AU - LI, Yao

PY - 2005

Y1 - 2005

N2 - This work explores neural networks (NN) based control approach to nonlinear flight systems in the presence of disturbances and uncertainties. Neuro-adaptive control incorporating with two neural network (NN) units is proposed to cope with NN reconstruction error and other lumped system uncertainties. It is shown that with the proposed strategy, the angles of attack, sideslip and body-axis roll of the vehicle are effectively controlled. The method does not involve analytical estimation of the upper bounds on ideal weights, reconstruction error, or nonlinear functions. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Analyses and simulations confirm the effectiveness of the proposed control scheme. © Springer-Verlag Berlin Heidelberg 2005.

AB - This work explores neural networks (NN) based control approach to nonlinear flight systems in the presence of disturbances and uncertainties. Neuro-adaptive control incorporating with two neural network (NN) units is proposed to cope with NN reconstruction error and other lumped system uncertainties. It is shown that with the proposed strategy, the angles of attack, sideslip and body-axis roll of the vehicle are effectively controlled. The method does not involve analytical estimation of the upper bounds on ideal weights, reconstruction error, or nonlinear functions. Stable on-line weight-tuning algorithms are derived based on Lyapunov's stability theory. Analyses and simulations confirm the effectiveness of the proposed control scheme. © Springer-Verlag Berlin Heidelberg 2005.

UR - https://www.scopus.com/pages/publications/24944470199

U2 - 10.1007/11427469_30

DO - 10.1007/11427469_30

M3 - Conference paper (refereed)

AN - SCOPUS:24944470199

SN - 9783540259145

SP - 192

EP - 197

BT - Advances in Neural Networks: ISNN 2005: Second International Symposium on Neural Networks. Proceedings

A2 - WANG, Jun

A2 - LIAO, Xiao-Feng

A2 - YI, Zhang

PB - Springer Berlin Heidelberg

ER -

Control of reusable launch vehicle using neuro-adaptive approach

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