Increase the Boost Converter Performance using Genetic Algorithms

The boost converter is widely used in applications of regulation of voltage and active power factor correction (PFC), its correct operation and final performance directly are related to the design of its closed loop control. The design of its loop control is quite complex due to the non-linearity of its behavior, the commutation of a switch (power transistor) makes its equivalent circuit to change continuously in the time (two circuits alternate in the time). In this work, the coefficients and poles of the closed loop transfer function for the average model (approximated linear model) of the boost converter are selected using the evolutionary principles of the genetic algorithms, with the purpose of improving the dynamic answer of the voltage regulator. The design scheme is successful verified by simulation and on a low power laboratory prototype, finding improvements in the dynamic performance (overvoltage and response time) in comparison with the classic scheme.