Implementation of Optimization-Based PI Controller Tuning for Non-Ideal Differential Boost Inverter

Abstract

The demand for renewable energy to sustain today’s vulnerability towards depleting fossil fuels is a crucial agenda for research. Various inverter topologies have been proposed to convert renewable sources into a usable form. But output THD, additional filtering components at line frequency (leading to bulky circuitry), lower efficiency, etc., are some of the limitations faced in all those topologies. This paper aims to change a voltage source inverter’s traditional behavior, which generates lesser output voltage with higher THD. The paper proposes a closed-loop non-ideal differential boost inverter (DBI) employing a PI controller. The optimization techniques such as, genetic algorithm (GA) and bacterial foraging optimization algorithm (BFOA) are incorporated to accentuate the PI controller’s performance to produce a better response during line and load disturbance conditions with reduced THD. DBI performance is evaluated on a laboratory prototype with different loading conditions. A comparison between the algorithms and the previous topologies from the literature survey has also been provided to validate this research’s claims. This paper’s required simulation study is carried out using MATLAB, and real-time validation is carried out using dSPACE 1104 with sampling time of one $\mu \text{s}$ .

Keywords

• Average modeling
• bacterial foraging optimization algorithm (BFOA)
• differential boost inverter (DBI)
• genetic algorithm (GA)
• small signal modeling
• tuning of PI controller