Implementing the induction-motor drive with four-switch inverter: An application of neural networks

This paper reports a four switch based three-phase voltage source inverter using space vector pulse width modulation (SVPWM), and designed with a three-layer feed forward back propagation based artificial neural network (ANN). The input–output samples, obtained using simulations in Matlab Simulink, were used for the extensive training of the neural network. Matlab interface with National Instruments’ NI-USB-6259 BNC was used for implementing the designed scheme with calculated weights and biases. The designed ANN based SVPWM model receives command voltage and reference speed as the inputs and generates pulse width modulated waves for the four-switch three-phase inverter bridge. The V/f ratio can be controlled by controlling the input parameters of the ANN generating PWM pulses. The simulations and experimental results, and harmonic analysis with the designed ANN structure are presented at different base speeds. The designed model was tested in under modulation, over modulation and unity modulation mode of operation and tuned to give minimum total harmonic distortion. Harmonic results at different modulation indexes are also presented. The ANN based implementation reduces the complexity of control system and overall cost reduction is achieved by the combination of FSTPI and ANN.

► Performance’ study of an ANN-based controller for a four-switch three-phase inverter.
► Reduced THD using space vector pulse width modulation.
► Performance deteriorates at low output frequencies.