PERFORMANCE ANALYSIS OF CASCADED MULTILEVEL INVERTER WITH PI AND NEURAL TECHNIQUES
PERFORMANCE ANALYSIS OF CASCADED MULTILEVEL INVERTER WITH PI AND NEURAL TECHNIQUES
- Neue Suche nach: Ramesh, M.
- Neue Suche nach: Kumar, R.Senthil
- Neue Suche nach: Maniraj, P.
- Neue Suche nach: Ramesh, M.
- Neue Suche nach: Kumar, R.Senthil
- Neue Suche nach: Maniraj, P.
The major problem in the electrical power quality is the harmonic content. There are several methods indicating the quantity of harmonic content and the most widely used measure is the Total Harmonic Distortion (THD). The open loop, conventional PI and neural network are designed for closed loop control of cascaded multilevel inverter to reduce the harmonics. The comparison is made for open loop and closed loop with PI and neural network. The comparison results reveal that the THD is reduced to about less than 5% with neural network control compared to open loop control. The mapping between the modulation rate and the required switching angles is learned and approximated with a feed forward neural network. After learning, appropriate switching angles can be determined by the neural network leading to a low-computational cost neural controller which is well suitable for real-time applications. This technique is applied for any number of levels of multilevel inverter. A nine level cascaded multilevel inverter power circuit is simulated in MATLAB 7.8 simulink with sinusoidal PWM technique. The results are presented and analyzed.
Dokumentinformationen
PERFORMANCE ANALYSIS OF CASCADED MULTILEVEL INVERTER WITH PI AND NEURAL TECHNIQUES
2016-09-01
doi:10.24297/jac.v12i17.2909
JOURNAL OF ADVANCES IN CHEMISTRY; Vol. 12 No. 17 (2016); 4992-5001 ; 2321-807X
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| DDC: | 629 |
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