Adaptive neural network path tracking of unmanned ground vehicle

Xiaohong LIAO; Zhao SUN; Liguo WENG; Bin LI; Yongduan SONG; Yao LI

doi:10.1007/11760023_179

Adaptive neural network path tracking of unmanned ground vehicle

Xiaohong LIAO^*
, Zhao SUN
, Liguo WENG
, Bin LI
, Yongduan SONG
, 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

Unmanned ground vehicles (UGVs) play an increasingly important role in future space exploration and battlefield. This work is concerned with the automatic path tracking control of UGVs. By using the structure properties of the system, neuro-adaptive control algorithms are developed for high precision tracking without involving complex design procedures - the proposed control scheme only demands partial information of the system, no detail description of the system model is needed. Furthermore, uncertain effects such as external disturbance and uncertain parameters can easily be handled. In addition, all the internal signals are uniformly bounded and the control torque is smooth anywhere. © Springer-Verlag Berlin Heidelberg 2006.

Original language	English
Title of host publication	Advances in Neural Networks: ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II
Editors	Jun WANG, Zhang YI, Jacek M. ZURADA, Bao-Liang LU, Hujun YIN
Publisher	Springer Berlin Heidelberg
Pages	1233-1238
Number of pages	6
ISBN (Electronic)	9783540344384
ISBN (Print)	9783540344377
DOIs	https://doi.org/10.1007/11760023_179
Publication status	Published - 2006
Externally published	Yes

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10.1007/11760023_179

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LIAO, X., SUN, Z., WENG, L., LI, B., SONG, Y., & LI, Y. (2006). Adaptive neural network path tracking of unmanned ground vehicle. In J. WANG, Z. YI, J. M. ZURADA, B.-L. LU, & H. YIN (Eds.), Advances in Neural Networks: ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II (pp. 1233-1238). Springer Berlin Heidelberg. https://doi.org/10.1007/11760023_179

@inproceedings{156d2833d0474bdca7fd7c895ce09b9b,

title = "Adaptive neural network path tracking of unmanned ground vehicle",

abstract = "Unmanned ground vehicles (UGVs) play an increasingly important role in future space exploration and battlefield. This work is concerned with the automatic path tracking control of UGVs. By using the structure properties of the system, neuro-adaptive control algorithms are developed for high precision tracking without involving complex design procedures - the proposed control scheme only demands partial information of the system, no detail description of the system model is needed. Furthermore, uncertain effects such as external disturbance and uncertain parameters can easily be handled. In addition, all the internal signals are uniformly bounded and the control torque is smooth anywhere. {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.",

author = "Xiaohong LIAO and Zhao SUN and Liguo WENG and Bin LI and Yongduan SONG and Yao LI",

year = "2006",

doi = "10.1007/11760023\_179",

language = "English",

isbn = "9783540344377",

pages = "1233--1238",

editor = "Jun WANG and Zhang YI and ZURADA, \{Jacek M.\} and Bao-Liang LU and Hujun YIN",

booktitle = "Advances in Neural Networks: ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II",

publisher = "Springer Berlin Heidelberg",

}

LIAO, X, SUN, Z, WENG, L, LI, B, SONG, Y & LI, Y 2006, Adaptive neural network path tracking of unmanned ground vehicle. in J WANG, Z YI, JM ZURADA, B-L LU & H YIN (eds), Advances in Neural Networks: ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II. Springer Berlin Heidelberg, pp. 1233-1238. https://doi.org/10.1007/11760023_179

Adaptive neural network path tracking of unmanned ground vehicle. / LIAO, Xiaohong; SUN, Zhao; WENG, Liguo et al.
Advances in Neural Networks: ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II. ed. / Jun WANG; Zhang YI; Jacek M. ZURADA; Bao-Liang LU; Hujun YIN. Springer Berlin Heidelberg, 2006. p. 1233-1238.

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

TY - GEN

T1 - Adaptive neural network path tracking of unmanned ground vehicle

AU - LIAO, Xiaohong

AU - SUN, Zhao

AU - WENG, Liguo

AU - LI, Bin

AU - SONG, Yongduan

AU - LI, Yao

PY - 2006

Y1 - 2006

N2 - Unmanned ground vehicles (UGVs) play an increasingly important role in future space exploration and battlefield. This work is concerned with the automatic path tracking control of UGVs. By using the structure properties of the system, neuro-adaptive control algorithms are developed for high precision tracking without involving complex design procedures - the proposed control scheme only demands partial information of the system, no detail description of the system model is needed. Furthermore, uncertain effects such as external disturbance and uncertain parameters can easily be handled. In addition, all the internal signals are uniformly bounded and the control torque is smooth anywhere. © Springer-Verlag Berlin Heidelberg 2006.

AB - Unmanned ground vehicles (UGVs) play an increasingly important role in future space exploration and battlefield. This work is concerned with the automatic path tracking control of UGVs. By using the structure properties of the system, neuro-adaptive control algorithms are developed for high precision tracking without involving complex design procedures - the proposed control scheme only demands partial information of the system, no detail description of the system model is needed. Furthermore, uncertain effects such as external disturbance and uncertain parameters can easily be handled. In addition, all the internal signals are uniformly bounded and the control torque is smooth anywhere. © Springer-Verlag Berlin Heidelberg 2006.

UR - https://www.scopus.com/pages/publications/33745915234

U2 - 10.1007/11760023_179

DO - 10.1007/11760023_179

M3 - Conference paper (refereed)

AN - SCOPUS:33745915234

SN - 9783540344377

SP - 1233

EP - 1238

BT - Advances in Neural Networks: ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part II

A2 - WANG, Jun

A2 - YI, Zhang

A2 - ZURADA, Jacek M.

A2 - LU, Bao-Liang

A2 - YIN, Hujun

PB - Springer Berlin Heidelberg

ER -

Adaptive neural network path tracking of unmanned ground vehicle

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