Improved Mountain Gazelle Optimization for PID Tuning of Solar Photovoltaic based Boost Converter

Nowadays, solar photovoltaic (PV) systems are used worldwide for clean production of electricity. The solar energy source is abundant in many countries. The dc-dc power electronic converters find major application in these solar PV systems. A good controller is necessary to control the power converters, where proportional integral derivative (PID) controller is more simple and easy to implement. Tuning of PID controller is an important job to ensure good performance of the system. In this paper a PID controller is designed for the dc-dc boost converter using improved Mountain Gazelle Optimization (MGO) algorithm. The dc-dc converter system with PID controller tuned using improved MGO algorithm is implemented using MATLAB/SIMULINK. The performance is compared with other PID controllers tuned using other popular optimization algorithms such as Grey Wolf Optimization (GWO) and Genetic Algorithm (GA) optimization. It is observed that the boost converter with PID controller tuned using improved MGO provides better output voltage tracking performance.