Neuro-fuzzy controlled Induction Generator system

Author

Sabreen, S.N. ; Malleswaran, M.

Author_Institution

Dept of Electr. Eng., Anna Univ. of Technol. Tirunelveli, Tirunelveli, India

fYear

2011

fDate

Feb. 28 2011-March 3 2011

Firstpage

1

Lastpage

5

Abstract

A Recurrent Functional-Link (FL) based Fuzzy Neural Network (FNN) controller with is proposed in this work to control a three phase Induction Generator (IG) system for stand-alone power application. The ac/dc power converter and a dc/ac power inverter are developed to convert the electric power generated by a three-phase IG from variable frequency and variable voltage to constant frequency and constant voltage, respectively. Moreover, two online-trained recurrent FL-based FNNs are introduced as the regulating controllers for both the dc-link voltage of the ac/dc power converter and the ac line voltage of the dc/ac power inverter. Finally, some simulation results are provided to demonstrate the effectiveness of the proposed recurrent FL-based FNN-controlled Induction Generator system.

Keywords

AC-DC power convertors; DC-AC power convertors; asynchronous generators; fuzzy control; fuzzy neural nets; machine control; neurocontrollers; recurrent neural nets; AC line voltage; AC-DC power converter; DC link voltage; DC-AC power inverter; constant frequency; constant voltage; electric power generation; fuzzy neural network controller; induction generator system; recurrent functional link; stand-alone power; variable frequency; variable voltage; Artificial neural networks; Fuzzy control; Fuzzy neural networks; Inverters; Rotors; Voltage control; Wind turbines; Functional-link neural network (FLNN); induction generator (IG);

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE), 2011 2nd International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4577-0786-5

Type

conf

DOI

10.1109/WIRELESSVITAE.2011.5940873

Filename

5940873