@inproceedings{dce7b3ff30564d41a39b5b0a5c1b64a5,
title = "Neural network model identification for actuators in a flight control systems",
abstract = "The precision system identification models is very important to design and analysis for complex control systems. A model of the actuators in a flight control systems is identified by using BP neural network. An adaptive BP neural network learning algorithm is proposed in this paper, which uses adaptive learn rate and steepest gradient optimization algorithm to train the weights. The improved algorithm is applied to identify the nonlinear actuators. The simulation results show that the performance of the neural network is improved effectively and the output of systems can be identified accurately by using the improved method.",
keywords = "Actuators, Adaptive gradient optimization algorithm, BP neural networks, Model identification",
author = "Zhiyi Huang and Wei Gu and Weiguo Zhang and Xiaoxiong Liu",
year = "2010",
doi = "10.1109/ICCASM.2010.5622899",
language = "英语",
isbn = "9781424472369",
series = "ICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings",
pages = "V13555--V13558",
booktitle = "ICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings",
note = "2010 International Conference on Computer Application and System Modeling, ICCASM 2010 ; Conference date: 22-10-2010 Through 24-10-2010",
}