A novel timing control method for neural network based digitally controlled DC-DC converter

Generally, the training based control method for dc-dc converters has a problem due to the fact that there is a difference of behavior between a controlled system before the training and one after the training. Therefore, when it is adopted to improve the transient response of dc-dc converter, it is needed to consider the bad effect of the training since the training term does not take its own effect to the transient response into account. Especially, the suitable timing and duration of the training based control term is affected since the behavior of the system is changed by its own effect. In this paper, we study a timing control method for a neural network based digital control method to improve the transient response of dc-dc converters. The neural network control is a suitable training based method since it can be a time series predictor to compensate the transient response. In our presented method, the standard three-layer neural network is adopted to improve the transient response converters by reference modification of a conventional PID control. To address the problem about the timing control, we present a method to obtain the suitable timing and duration effect of the neural network control term with simple criteria. This timing control works to avoid the bad effect of the neural network control term and obtain improved results. Experimental results show that our method can contribute to the improvement of transient response effectively.