S.L. Kek
Universiti Tun Hussein Onn Malaysia

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Enhance Cascaded H-Bridge Multilevel Inverter with Artificial Intelligence Control S.Y. Sim; C.K. Chia; W.M. Utomo; H.H. Goh; Y.M.Y. Buswig; A.J.M.S. Lim; S.L. Kek; A.A. Bohari; C.L, Cham
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp105-112

Abstract

This paper proposed a 7-level Cascaded H-Bridge Multilevel Inverter (CHBMI) with two diffenrent controller, ie, PID and Artificial Neural Network (ANN) controller to improve the output voltage performance and achieve a lower Total Harmonic Distortion (THD). A PWM generator is connected to the 7-level CHBMI to provide switching of the MOSFET. The reference signal waveform for the PWM generator is set to be sinusoidal to obtain an ideal AC output voltage waveform from the CHBMI. By tuning the PID controller as well as the self-learning abilities of the ANN controller, switching signals towards the CHBMI can be improved.  Simulation results from the general CHBMI together with the proposed PID and ANN controller based 7-level CHBMI models will be compared and discussed to verifyl the proposed ANN controller based 7-level CHBMI achieved a lower output voltage THD value with a better sinusoidal output performance.