Enhance the accuracy of control algorithm for multilevel inverter based on artificial neural network

In converters or multilevel inverters it is very important to ensure that the output of the multilevel inverters waveforms in term of the voltage or current of the waveforms is smooth and without distortion. The artificial neural network (ANN) technique to obtaining proper switching angles sequences for a uniform step asymmetrical modified multilevel inverter by eliminating specified higher-order harmonics while maintaining the required fundamental voltage and current waveform. However, through this paper a modified CHB-MLI are proposed using artificial intelligence optimization technique based on modulation selective harmonic elimination (SHE-PWM). A most powerful modulation technique that used to minimize a harmonic contants during the outout waveform of multilevel inverter is a SHE-PWM method. The proposed a five-level modified cascaded H-bridge multilevel inverter (M-CHBMI) with ANN controller to improve the output voltage and current performance and achieve a lower total harmonic distortion (THD). The main aims of this paper cover design, modeling, prediction for real-time generation of optimal switching angles in a single-phase topology of modified five level CHB-MLI. Due to the heavy cost of computation to solving transcendental nonlinear equations with specified number, a real-time application of selective harmonic elimination-pulse width modulation (SHEPWM) technique is limited. SHE equations known as a transcendental nonlinear equation that contain trigonometric functions. The prototype of a 5- level inverter in digital signal processing (DSP) TMS320F2812 reveals that the proposed method is highly efficient for harmonic reduction in modified multilevel inverter.