Renewable resources when utilized provide only DC power as output. In maximum cases, this DC power cannot be fed directly to industrial or domestic loads. Therefore, there is a need to convert this constant DC supply to AC waveform and to boost the available supply voltage to meet the load requirements. By far the DC-AC boost inverter is the most efficient-it converts the DC voltage into AC voltage and boosts the voltage in a single stage. The AC output voltage is an almost pure sinusoidal waveform. In this work, the genetic algorithm has been used to tune the proportional constant (Kp-and integral constant (Ki-of the proportional integral (PI) controller used in the small signal model voltage mode control of the boost inverter system. This is a novel approach and it has been attempted with success as algorithm based small signal modelling has not been attempted before in research related to boost inverter topology. The stability of the proposed system is tested using a simulation model and a prototype inverter model. Results obtained from the genetic algorithm based small signal voltage mode controlled boost inverter model is then compared with the results from the traditional boost inverter model implemented using small signal voltage mode control. In the traditional boost inverter, the Zeigler Nichol's method has been used to tune the controller constants. Adaptability of the controller constants in both the models are checked by analyzing the respective boost inverter systems during steady state testing, line voltage variation and load disturbance conditions. © 2016 American Scientific Publishers All rights reserved.