A new digital control DC-DC converter with repetition neural network prediction

This paper presents a novel prediction based digital control dc-dc converter. In this method, a neural network control is adopted to improve the transient response in coordination with a conventional P-I-D control. The prediction based control term is consists of predicted data which are obtained from repetitive training of the neural network. This works to improve the transient response very effectively when the load is changed quickly. As a result, the undershoot and convergence time of the output voltage and the overshoot of the reactor current are suppressed effectively as compared with the conventional one in the step change of load resistance.