Real-time implementation of an on-line trained neural network controller for power electronics converters
K. T. Chau, C.C. Chan · 2002
Since power electronics converters behave nonlinearly, conventional control strategies such as PID are incapable of obtaining good dynamical performance. This paper addresses implemention of on-line trained neural networks for power electronics converters. A PWM boost converter is used as an example. Real-time implementation of the neural networks is accomplished by using a powerful digital signal processor. The converter is operated as a power amplifier and a power regulator. Both computer simulation and experimental results show that good dynamical performance can be obtained.>