GA-based optimization and ANN-based SHEPWM generation for two-level inverter - Deniz, Erkan; Aydogmus, Omur; Aydogmus, Zafer (Institute of Electrical and Electronics Engineers Inc., 2015)
Selective harmonic elimination (SHE) is a well-known PWM technique applied voltage source inverters (VSI) to control fundamental voltage and eliminate chosen harmonics. This technique requires the determination of optimum switching angles by solving the nonlinear equation set and a look-up table stored the switching times in a real-time application. This paper presents a hybrid genetic algorithm (GA) to optimize offline of optimum 11-switching angles for three-phase two-level inverter. In addition, the paper proposes two Artificial Neural Networks (ANN) based solution. The first ANN was trained by the data obtained from GA to calculate the switching angles without using a look-up table. Second ANN was trained by using these switching angles to generate PWM signals. GA and ANN are performed by using MATLAB environment. The ANN-based SHEPWM was designed to obtain inverter output voltage which has a bipolar waveform with quarter-wave symmetry. The waveforms of inverter output voltage and load current are analyzed with FFT for a RL load. © 2015 IEEE.
2015 IEEE International Conference on Industrial Technology, ICIT 2015 -- 17 March 2015 through 19 March 2015 -- Seville -- 112951
Keywords: Artificial neural network (ANN); Genetic algorithm; MATLAB GA-toolbox; Selective harmonic elimination (SHE)