An EGA Approach-Based Fractional Order PID Controller for Synchronous Buck Converters

Abstract

In this paper, an enhanced genetic algorithm (EGA) technique-based fractional order PID controller (FOPID) for simultaneous control of synchronous buck converters is proposed. The novelty of EGA method is that enhancement process is done by the Rat swarm algorithm (RSA). The computational scheme of RSA is used to enhance the performance of traditional genetic algorithm (GA) and a modified version of GA, which is used for optimal tuning of FOPID controller. In the proposed methodology, the FOPID controller gain is adjusted to achieve the preferred response that is demonstrated by EGA technique. The objective of the proposed technique is “the smooth DC output voltage is attained under damped response”. The proposed control method is executed and simulated in MATLAB platform and the performance is analyzed with the existing methods. Statistical analysis of mean, median and standard deviation for the proposed and existing methods is also analyzed. The proposed FOPID controller produces regulated output DC voltage having 34% lesser overshoots and two times faster settling time when compared to the existing dynamic evolution controller for Synchronous Buck Converters (SBCs). The designed optimal FOPID controlled SBC is also implemented in hardware using Atmega16A processor for different loading conditions for better applications.