Robot tracking in task space using neural networks
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Detail(s)
Original language | English |
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Title of host publication | IEEE International Conference on Neural Networks - Conference Proceedings |
Publisher | IEEE |
Pages | 2854-2858 |
Volume | 5 |
Publication status | Published - 1994 |
Externally published | Yes |
Publication series
Name | |
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Volume | 5 |
Conference
Title | Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) |
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City | Orlando, FL, USA |
Period | 27 - 29 June 1994 |
Link(s)
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 IEEE, 1994. p. 2854-2858.Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review