Fuzzy and Neural Network Method of Identification for Closed-Loop and Non-Linear Object

马革新; 张大力; 李衍达

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Fuzzy and Neural Network Method of Identification for Closed-Loop and Non-Linear Object

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- Fuzzy and Neural Network Method of Identification for Closed-Loop and Non-Linear Object
- Acta Electronica Sinica Issue 5, Pages: 109-112(1998)
- 作者机构：
  
  1. 清华大学自动化系!北京
  2. 100084
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Published：1998
- 稿件说明：
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[1]马革新,张大力,李衍达.闭环非线性对象辨识的模糊和神经网络方法[J].电子学报,1998(05):109-112.

马革新, 张大力, 李衍达. Fuzzy and Neural Network Method of Identification for Closed-Loop and Non-Linear Object[J]. Acta Electronica Sinica, 1998, (5): 109-112.
[1]马革新,张大力,李衍达.闭环非线性对象辨识的模糊和神经网络方法[J].电子学报,1998(05):109-112. DOI：

马革新, 张大力, 李衍达. Fuzzy and Neural Network Method of Identification for Closed-Loop and Non-Linear Object[J]. Acta Electronica Sinica, 1998, (5): 109-112. DOI：

摘要

闭环系统的辨识是近年来在国内很受重视的研究课题．本文基于闭环对象的历史数据，采用模糊方法构造系统的初始模型，以克服闭环数据稀疏给系统辨识带来的困难，并基于现场数据，采用OLS算法对初始模型进行修正，以提高系统的辨识精度．将这种方法应用于某合成氨过程的实际数据，得到了良好的辨识效果．

Abstract

There is much interest in closed-loop system identification recently. In this paper

based on historical input and output data

an initial model using fuzzy method is constructed to encounter the difficulty of sparse identification data. The initial model is then enhanced by a radial basis function neural network model trained using input-output data. The new identification method is used in real data from an ammonia process with satisfactory results.

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