@inproceedings{9b53d8d3262d45cabeea121d11cd7680,
title = "Robust adaptive neural networks with an online learning technique for robot control",
abstract = "A new robust adaptive neural networks tracking control with online learning controller is proposed for robot systems. A learning strategy and robust adaptive neural networks are combined into a hybrid robust control scheme. The proposed controller deals mainly with external disturbances and nonlinear uncertainty in motion control. A neural network (NN) is used to approximate the uncertainties in a robotic system. Then the disadvantageous effects on tracking performance, due to the approximating error of the NN in robotic system, are attenuated to a prescribed level by an adaptive robust controller. The learning techniques of NN will improve robustness with respect to uncertainty of system, as a result, improving the dynamic performance of robot system. A simulation example demonstrates the effectiveness of the proposed control strategy.",
author = "Yu, \{Zhi Gang\} and Song, \{Shen Min\} and Duan, \{Guang Ren\} and Run Pei",
year = "2006",
doi = "10.1007/11760023\_169",
language = "英语",
isbn = "3540344373",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1153--1159",
booktitle = "Advances in Neural Networks - ISNN 2006",
address = "德国",
note = "3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks ; Conference date: 28-05-2006 Through 01-06-2006",
}