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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Daryabeigi, E. Emanian, A. Namazi, M.M. Rashidi, A. Saghaian-Nejad, S.M. |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Electrical and Computer Engineering, Isfahan, University of Technology, Isfahan, Iran (Emanian, A.; Rashidi, A.; Saghaian-Nejad, S.M.) || Department of Electrical engineering, Tiran branch, Islamic Azad University, Tiran, Iran (Daryabeigi, E.; Namazi, M.M.) |
| Abstract | This paper presents a modern control system for switched reluctance motor (SRM) drives. The control system is based on computational model of mammalian limbic system and emotional processes (BELBIC) which is presented as speed controller of the motor drive with attention to torque ripple decrease. In this work, a novel and simple model of SRM drives control plant is achieved by using the intelligent control system, which controls motor speed accurately and directly, without needing to use any conventional controllers and also, quite independent of the motor parameters. Then, proposed method is compared with a conventional PI controller and sliding mode as a nonlinear approach, which shows its advantages than both of them. The performance of the proposed controller is demonstrated by simulation and experimental results using a 4kW, four-phase, 8/6 pole SRM DSP-based drive system. This generation of the intelligent controllers that has high auto learning speed with simple structure shows excellent praxis for industrial scale utilization truly. |
| Starting Page | 1528 |
| Ending Page | 1535 |
| File Size | 865022 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781457712159 |
| e-ISBN | 9781457712166 |
| e-ISBN | 9781457712142 |
| DOI | 10.1109/APEC.2012.6166023 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-02-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Reluctance motors Brain modeling Torque Computational modeling Mathematical model Control systems |
| Content Type | Text |
| Resource Type | Article |
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