Modeling of Nonlinear System with Optimized Structure Based on BP Neural Network Model and Simulation

被引：0

作者：

Zhou Li ^{[1
]}

Qu Dongcai ^{[1
]}

Cheng Jihong ^{[1
]}

机构：

[1] Ludong Univ, Sch Management, Yantai 264025, Peoples R China

来源：

PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1-2 | 2008年

关键词：

Nonlinear system; neural networks (NN); model reference adaptive control (MRAC); simulation;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

After identification principle based on BP neural networks for nonlinear system was analysed, using simulation method, the influence of identification modeling with different BP neural networks model structures was studied. Through optimized to initial BP network model structure designed, the reasonable and optimized network structure was obtained, and simulation effects of identification modeling were compared with no optimized the BP neural network structure model. Simulation results show that the error of optimized BP neural network model is reduced, the generalization ability of network model is enhanced.

引用

页码：1017 / 1020

页数：4

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