Neuro-fuzzy-based space vector modulation for THD reduction in VSI fed induction motor drive Online publication date: Sat, 23-Aug-2014
by G. Durgasukumar; Mukesh Kumar Pathak
International Journal of Power Electronics (IJPELEC), Vol. 4, No. 2, 2012
Abstract: Space vector modulation is an optimal pulse width modulation technique for variable speed drive application. This paper proposes adaptive neuro-fuzzy inference system (ANFIS) based space vector modulation (SVM) technique for voltage source inverter. The proposed ANFIS network is independent of the switching frequency and uses hybrid learning algorithm for training. Due to this learning algorithm, SVM algorithm can be implemented very fast and the desired training error can be obtained with less number of iterations compared to other optimisation techniques like neural, fuzzy and genetic. The performance of ANFIS controlled drive is compared with the conventional SVM-based drive. The simulation results of inverter phase voltages obtained are verified experimentally using a Dspace kit (DS1104). The % THD value of simulation and experimental waveforms of inverter phase voltages for 3 kHz switching frequency is presented.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Power Electronics (IJPELEC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook