By Topic

Hybrid Bacterial Foraging Optimization Strategy for Automated Experimental Control Design in Electrical Drives

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Okaeme, N.A. ; Alstom Grid, Stafford, UK ; Zanchetta, P.

This paper explores the automated experimental control design for variable speed drives using a novel heuristic optimization algorithm. A hybrid approach, which combines desirable characteristics of two of the most widely used biologically-inspired heuristic algorithms, the genetic algorithms (GAs) and the bacterial foraging (BF) algorithms, is studied and developed in this paper. Both the structures and parameters of digital speed controllers are optimized experimentally and directly on the drive while it is subject to different types of mechanical load; the dynamics of these load profiles are generated using a programmable load emulator. The proposed hybrid bacterial foraging (HBF) algorithm is evaluated, for the purpose of control optimization for electric drives, against GA and BF, and their performances are compared and contrasted.

Published in:

Industrial Informatics, IEEE Transactions on  (Volume:9 ,  Issue: 2 )