Research of Speed Observer Based on Neural Network Optimized by Fast Modified ACO in DTCs

Author

Cao, Chengzhi ; Jia, Lichao ; San, Hongli ; You, Ying

Author_Institution

Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang

Volume

1

fYear

2008

fDate

20-22 Dec. 2008

Firstpage

18

Lastpage

22

Abstract

To enhance its global optimization speed, the basic ant colony optimization (ACO) is modified, then it is used to optimize the neural networks (NN), and the optimized NN is applied to the direct torque control (DTC) system, so that the rotate speed can be observed. The DTC with speed sensorless is implemented at last. The research of simulation shows that, the modified ACO has eminent global optimization performance and fast convergence rate, the rotate speed of the system is able to be observed by the DTC system with the NN optimized by this method exactly, thereby, the DTC with speed sensorless can be implement.

Keywords

neurocontrollers; observers; optimisation; torque control; ant colony optimization; direct torque control; fast modified ACO; global optimization; neural network; speed observer; Ant colony optimization; Control theory; Convergence; Information science; Information technology; Intelligent networks; Neural networks; Optimization methods; Robustness; Torque control; DTC; Neural Network; ant colony optimization; speed observer;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3497-8

Type

conf

DOI

10.1109/IITA.2008.33

Filename

4739527