A PID control scheme with enhanced non-dominated sorting genetic algorithm applied to a non-inverting buck-boost converter

The non-inverting buck-boost converter is designed to regulate the output voltage of the non-linear converter in real-time applications. Numerous studies have been carried out in recent years to improve the dynamic behavior of converters using intelligent control techniques; still, the occurrence of large overshoots in transient and reduction of ripple over voltage has not been effectively discussed. This can be efficiently handled by selecting filter capacitance values effectively. This article proposes a design of a Proportional-integral-derivative controller optimized by a non-dominated sorting genetic algorithm (NSGA) and enhanced non-dominated sorting genetic algorithm (ENSGA) to choose the filter capacitance value and to maintain the converter output voltage at the desired level. A dynamic crowding distance-based ENSGA has been employed to attain the homogenous distribution of non-dominated solutions. The stability of the buck-boost mode is analyzed using frequency response. Based on the simulation results obtained for various load conditions, the ENSGA controller outperformed the NSGA controller in terms of better output voltage regulation, lesser transients, and minimizing the ripple voltage.