DocumentCode :
2916466
Title :
Neural network inverse control of variable frequency speed-regulating system in V/F mode
Author :
Dai, Xianzhong ; Liu, Guohai ; Zhang, Hao ; Zhang, Xinghua
Author_Institution :
Dept. of Autom. Control, Southeast Univ., Nanjing, China
fYear :
2005
fDate :
6-10 Nov. 2005
Abstract :
An induction motor driven by a normal and low-cost inverter running in V/F mode, named as a variable frequency speed-regulating system in V/F, is widely used, but its control performance is not good enough to meet the needs of speed-regulation. So it is useful to improve its control performance without changing the original structure of variable frequency speed-regulating system (VFSRS). Considering the induction motor and the inverter as a whole controlled object, a mathematic model of such variable frequency speed-regulating system in V/F and its inverse model, with or without compensation, are given in this paper. Constructing a neural network inverse and combining it with the variable frequency speed-regulating system in V/F, a pseudo-linear system is completed. Then a linear close-loop adjuster is designed to obtain a better speed-regulating performance. Results of experiments demonstrate that speed-regulating performances can be greatly improved using this simple method.
Keywords :
angular velocity control; closed loop systems; electric machine analysis computing; frequency control; induction motors; invertors; linear systems; machine control; neural nets; V-F mode; induction motor; inverse model; linear close-loop adjuster; low-cost inverter; mathematic model; neural network inverse control; pseudolinear system; variable frequency speed-regulating system; Chemical industry; Control systems; Electric variables control; Frequency; Induction motors; Intelligent networks; Inverters; Machine vector control; Neural networks; Nonlinear control systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, 2005. IECON 2005. 31st Annual Conference of IEEE
Print_ISBN :
0-7803-9252-3
Type :
conf
DOI :
10.1109/IECON.2005.1569161
Filename :
1569161
Link To Document :
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