| dc.contributor.author | Veena, P | |
| dc.contributor.author | Jeyabharath, R | |
| dc.contributor.author | Rajaram, M | |
| dc.contributor.author | Sivanandam, S.N. | |
| dc.date.accessioned | 2009-11-17T08:49:36Z | |
| dc.date.available | 2009-11-17T08:49:36Z | |
| dc.date.issued | 2009-10-11 | |
| dc.identifier.citation | p.2B5 1 - 2B5 2 | en_US |
| dc.identifier.uri | http://dspace.unimap.edu.my/123456789/7318 | |
| dc.description | Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. | en_US |
| dc.description.abstract | Direct torque control (DTC) of Switched reluctance motor is known to have simple control structure with comparable performance. However, the role of optimal
selection of the voltage space vector is one of the weakest points in a conventional DTC drive. In this paper optimal selection of
voltage space vectors is achieved using GA based neural network. Simulations results validate the proposed intelligent system with fast torque and flux response with minimized torque and flux ripple. | en_US |
| dc.description.sponsorship | Technical sponsored by IEEE Malaysia Section | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Universiti Malaysia Perlis | en_US |
| dc.relation.ispartofseries | Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) | en_US |
| dc.subject | Direct torque control | en_US |
| dc.subject | Flux control | en_US |
| dc.subject | Genetic algorithms | en_US |
| dc.subject | Neuro controller | en_US |
| dc.subject | Switched reluctance Motor | en_US |
| dc.subject | Electric driving -- Automatic control | en_US |
| dc.subject | Electric machinery -- Alternating current -- Automatic control | en_US |
| dc.title | Genetic neuro controller based direct torque control for switched reluctance motor drive | en_US |
| dc.type | Working Paper | en_US |
| dc.contributor.url | veena_gce@yahoo.co.in | en_US |
