PID Tuning Of Automatic Voltage Regulator Using MFO And WOA Techniques

Abstract

In this paper, two novel artificial intelligence based optimization methods Moth Flame Optimization (MFO) and Whale Optimization Algorithm (WOA) are applied and compared in terms of proportional, integral and derivative controller parameters for the improvement of dynamic performance of power utility of an Automatic Voltage Regulator(AVR).For multi-variable and multi-objective prob- lems as in the case of AVR, the evolutionary algorithm of optimization becomes   a solution. But in many cases, the use of conventional optimization methods is difficult for system optimization due to various parameter dependencies which makes MFO and WOA  both very feasible and reliable as these belong to the  most promising Swarm Intelligence Optimization family whose variants are easy to understand and simple to operate. Navigation methodology followed by the moths is the main inspiration for MFO technique to be used. Moths fly at night with the maintenance of a fixed angle with respect to the moon which makes it an effective method to move in a straight line for long distances. On the other handywoman is inspired by the hunting behavior of humpback whales. It includes three operators for simulation-The search for prey, encircling prey, and bubble  net foraging behavior of humpback whales. Here, we are comparing our results with very common algorithm which is Genetic algorithm.