EVOLUTIONARY ALGORITHMS FOR PID CONTROLLER DESIGN OF BOOST INVERTER IN PHOTOVOLTAIC APPLICATIONS

Abstract

This paper proposes a design method for determining the optimal proportional-integral-derivative (PID) controller parameters of a boost inverter using the evolutionary algorithms for photovoltaic (PV) system. This paper details how to employ the evolutionary algorithm to search efficiently the optimal PID controller parameters of boost inverter. A time-domain performance criterion function was used in order to assist estimating the optimal PID controller parameters. Comparison is made among the genetic algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony algorithm (ABC) and Particle Swarm Optimization (PSO). It is found that Particle Swarm Optimization algorithm based PID controller was indeed more efficient and robust in improving the step response of a boost inverter. Simulations are carried out and results are presented to validate the performance of the PID controller.

Keywords

• Ant Colony Optimization (ACO)
• Artificial Bee Colony Algorithm (ABC)
• Genetic Algorithm (GA)
• Particle Swarm Optimization (PSO)
• Proportional Integral Derivative (PID)