Robot tracking in task space using neural networks

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

19 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages2854-2858
Volume5
Publication statusPublished - 1994
Externally publishedYes

Publication series

Name
Volume5

Conference

TitleProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA
Period27 - 29 June 1994

Abstract

This paper considers tracking control of robots in task space. A new control scheme is proposed based on a kind of conventional controller and a neural network based compensating controller. This scheme takes advantages of simplicity of the model based control approach and uses the neural network controller to compensate for the robot modelling uncertainties. The neural network is trained on line based on Lyapunov theory and thus its convergence is guaranteed.

Citation Format(s)

Robot tracking in task space using neural networks. / Feng, Gang; Chak, C. K.
IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 5 Institute of Electrical and Electronics Engineers, Inc., 1994. p. 2854-2858.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review