Research on Optimization of Speed Identification Based on ACO-BP Neural Network and application

被引：1

作者：

Cao, Chengzhi ^{[1
]}

Wang, Yifan ^{[1
]}

Jia, Lichao ^{[1
]}

Liu, Yang ^{[1
]}

机构：

[1] Shenyang Univ Technol, Sch Informat Sci & Engn, Shenyang 110023, Liaoning Prov, Peoples R China

来源：

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年

关键词：

ant colony algorithm; neural network; direct torque control; speed identification;

D O I：

10.1109/WCICA.2008.4594574

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Introducing the rank-weight method into the basic ant colony optimization (ACO), we use the modified ACO to optimize the weights and thresholds value of neural networks (NN). And when the BPNN is being trained, this method can solve the disadvantages of running into the minimum easily, and enhance the convergence speed. So we get a heuristic method, which is good at time efficiency and derivation efficiency that is ACOrw-BP. Then this method was used to identify the speed of the motor in direct toque control (DTC). The results of the simulation showed that: the modified ACOrw-BP neural network not only has the ability of mapping widely, but also enhancing the operation efficiency obviously. The speed of the motor can be identified accurately by this method, and the result is good. So, it implements the direct toque control of speed sensorless.

引用

页码：6973 / 6977

页数：5

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