基于人工神经网络的状态估计

[1990] Proceedings. The Twenty-Second Southeastern Symposium on System Theory Pub Date : 1990-03-11 DOI:10.1109/SSST.1990.138206

A. Kanekar, A. Feliachi

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引用次数: 6

摘要

利用人工神经网络解决了状态估计问题。所使用的神经网络是自适应线性组合和多层网络。训练是通过使用几个卡尔曼滤波方案来设置不同的权值来完成的。推导出的神经网络估计器在系统受到未知噪声时给出状态估计。举例说明了所提出的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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State estimation using artificial neural networks

The state estimation problem is addressed using artificial neural networks. The neural networks used are the adaptive linear combiner and a multilayer net. Training is performed by using several Kalman filter solutions to set the different weights. The derived neural network estimator gives state estimates when the system is subjected to unknown noises. Examples are given to illustrate the proposed approach.<>

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[1990] Proceedings. The Twenty-Second Southeastern Symposium on System Theory

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