Performance Analysis of GA and PSO Based PI Controller for Cascaded H-bridge Multilevel Inverter Output Voltage Regulation

This paper presents a performance analysis of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) based Proportional-Integral (PI) controllers for regulating the output voltage of a Cascaded H-Bridge Multilevel Inverter (CHMI) during load variations. Proportional-Integral (PI) controller is the most common controller used to solve this issue due to its simple structure, high stability, minimal steady state error and ease of implementation. However, the performance of this controller is sensitive to parameter variation and has limited performance for nonlinear systems such as CHMI. The study aims to evaluate and compare the effectiveness of GA and PSO in achieving voltage regulation in the CHMI system using MATLAB Simulink. GA and PSO are applied to optimize the parameters of the PI controller to maintain the desired output voltage despite load variations. During load variations, PSO-PI have better voltage regulation compared to GA-PI and conventional PI by a margin of 0.31% and 3.52% respectively. The simulation results demonstrate that both GA and PSO based PI controllers effectively regulate the output voltage of the CHMI system during load variations. However, a comprehensive analysis reveals that the PSO algorithm outperforms the GA algorithm in terms of voltage regulation accuracy and response time.