Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/101797
Title: | Weight-varying neural network for parameter identification of automatic vehicle | Authors: | Huang, Lei Shi, Yikai Yuan, Xiaoqing Wang, Danwei Yu, Ming |
Keywords: | DRNTU::Engineering::Electrical and electronic engineering | Issue Date: | 2012 | Source: | Huang, L., Shi, Y., Yuan, X., Wang, D., & Yu, M. (2012). Weight-varying neural network for parameter identification of automatic vehicle. 2012 10th IEEE International Conference on Industrial Informatics (INDIN), pp.766-771. | Conference: | IEEE International Conference on Industrial Informatics (10th : 2012 : Beijing, China) | Abstract: | A Bond Graph model is built for the steering system of automatic vehicle and a set of model equations are derived for further analysis purpose. For identifying several uncertain parameters, an integrative approach that combine least square method with Bp Neural Network algorithm (NN) is proposed, based on features of NN algorithm, two key improvements are bring into the training method of Bp NN: taking the identification result of least square method as initial weight value of network training, and introducing weight factor to improve the convergence property of Bp NN. The effectiveness of proposed approach is verified through experiment, and the result indicates that the reformatory Bp NN algorithm has higher identification accuracy. | URI: | https://hdl.handle.net/10356/101797 http://hdl.handle.net/10220/16369 |
DOI: | 10.1109/INDIN.2012.6301243 | Schools: | School of Electrical and Electronic Engineering | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | EEE Conference Papers |
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