Robust tracking control of space robot via neural network

Feng Baomin; Ma Guangcheng; Xie Weinan; Wang Changhong

Robust tracking control of space robot via neural network

Feng Baomin^*
, Ma Guangcheng
, Xie Weinan
, Wang Changhong

^*Corresponding author for this work

School of Astronautics

Harbin Institute of Technology

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

8 Scopus citations

Abstract

This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties.

Original language	English
Title of host publication	1st International Symposium on Systems and Control in Aerospace and Astronautics
Pages	902-906
Number of pages	5
State	Published - 2006
Event	1st International Symposium on Systems and Control in Aerospace and Astronautics - Harbin, China Duration: 19 Jan 2006 → 21 Jan 2006

Publication series

Name	1st International Symposium on Systems and Control in Aerospace and Astronautics
Volume	2006

Conference

Conference	1st International Symposium on Systems and Control in Aerospace and Astronautics
Country/Territory	China
City	Harbin
Period	19/01/06 → 21/01/06

Cite this

@inproceedings{ec74888bd0284e82ad92f90761b25a4b,

title = "Robust tracking control of space robot via neural network",

abstract = "This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties.",

author = "Feng Baomin and Ma Guangcheng and Xie Weinan and Wang Changhong",

year = "2006",

language = "英语",

isbn = "0780393953",

series = "1st International Symposium on Systems and Control in Aerospace and Astronautics",

pages = "902--906",

booktitle = "1st International Symposium on Systems and Control in Aerospace and Astronautics",

note = "1st International Symposium on Systems and Control in Aerospace and Astronautics ; Conference date: 19-01-2006 Through 21-01-2006",

}

Baomin, F, Guangcheng, M , Weinan, X & Changhong, W 2006, Robust tracking control of space robot via neural network. in 1st International Symposium on Systems and Control in Aerospace and Astronautics., 1627472, 1st International Symposium on Systems and Control in Aerospace and Astronautics, vol. 2006, pp. 902-906, 1st International Symposium on Systems and Control in Aerospace and Astronautics, Harbin, China, 19/01/06.

Robust tracking control of space robot via neural network. / Baomin, Feng; Guangcheng, Ma ; Weinan, Xie et al.
1st International Symposium on Systems and Control in Aerospace and Astronautics. 2006. p. 902-906 1627472 (1st International Symposium on Systems and Control in Aerospace and Astronautics; Vol. 2006).

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

TY - GEN

T1 - Robust tracking control of space robot via neural network

AU - Baomin, Feng

AU - Guangcheng, Ma

AU - Weinan, Xie

AU - Changhong, Wang

PY - 2006

Y1 - 2006

N2 - This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties.

AB - This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties.

UR - https://www.scopus.com/pages/publications/33750939065

M3 - 会议稿件

AN - SCOPUS:33750939065

SN - 0780393953

SN - 9780780393950

T3 - 1st International Symposium on Systems and Control in Aerospace and Astronautics

SP - 902

EP - 906

BT - 1st International Symposium on Systems and Control in Aerospace and Astronautics

T2 - 1st International Symposium on Systems and Control in Aerospace and Astronautics

Y2 - 19 January 2006 through 21 January 2006

ER -

Robust tracking control of space robot via neural network

Abstract

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