Intelligent electric drive system

Author

Tamjis, M.R. ; Hew, W.P. ; Anas, M.R. ; Adnan, W.A.

Author_Institution

Fac. of Eng., Malaya Univ., Kuala Lumpur, Malaysia

Volume

3

fYear

2000

fDate

2000

Firstpage

334

Abstract

To simplify the neurocontrol and to speed up the learning process, a new neural network with very simple structure and shorter learning time is proposed in this paper. The learning algorithm adopted is a space vector searching approach based on the competitive learning principle. The fuzzy logic and neural network are used to produce the optimum output from a vector control scheme, which determines the switching pattern of an inverter driver. The main aim of this paper is to focus on the outcome and results of simulations based on fuzzy logic and neural network

Keywords

DC-AC power convertors; control system analysis; control system synthesis; fuzzy control; fuzzy neural nets; induction motor drives; intelligent control; invertors; machine theory; machine vector control; neurocontrollers; unsupervised learning; variable speed drives; velocity control; competitive learning principle; control design; control simulation; fuzzy logic; intelligent electric drive system; invertor driver switching pattern; learning algorithm; learning process; learning time; neural network; neurocontrol; space vector searching approach; speed regulation; variable speed induction motor drives; vector control scheme; Error correction; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Induction motors; Intelligent systems; Inverters; Neural networks; Pi control;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2000. Proceedings

Conference_Location

Kuala Lumpur

Print_ISBN

0-7803-6355-8

Type

conf

DOI

10.1109/TENCON.2000.892284

Filename

892284