Optimization of an analog controller for a solar tracker using genetic algorithms and particle swarm optimization

This paper shows the design and implementation of an analog controller for a solar tracker. The kind of controller implemented consists of a pole, a zero and gain. The calculation of controller parameters is performed by bio-inspired optimization algorithms. In particular are used Particle Swarm Optimization and Genetic Algorithms. This seeks to observe the performance that these two types of algorithms has for this class of applications. The comparison of results for the algorithms is performed statistically.