International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 46 - Number 19 |
Year of Publication: 2012 |
Authors: Mitali Shrivastava, Varsha Singh, Swapnajit Pattnaik |
10.5120/7050-9710 |
Mitali Shrivastava, Varsha Singh, Swapnajit Pattnaik . Comparative Analysis of PWM Techniques for Multilevel Inverter Control using ANN. International Journal of Computer Applications. 46, 19 ( May 2012), 20-24. DOI=10.5120/7050-9710
This paper proposes a comparative analysis of sinusoidal PWM and selective harmonic elimination PWM for the control of cascaded multilevel inverters. A novel concept of application of Artificial Neural Networks (ANN) for estimating the optimum switching angles for cascaded multilevel inverters is presented. In this paper, the ANN is trained off-line using the desired switching angles given by the classic harmonic elimination strategy to any value of the modulation index. After training the proposed ANN system, a large and memory-demanding look-up table is replaced with trained neural network to generate the optimum switching angles with lowest THD for a range of modulation index. This technique can be applied to multilevel inverters with any number of levels. As an example, a seven-level and eleven-level inverter is considered and the optimum switching angles are calculated, in order to eliminate the odd harmonics and to reduce THD. To verify these goals, the system is simulated on MATLAB/ Simulink. The ANN control algorithm is implemented using m-file program. Theoretical analysis of the proposed algorithm with neural networks is provided, and simulation results of SPWM and SHE-PWM techniques are compared to show the improved performance and technical advantages of the developed system.