A New Prediction Based Digital Control for DC-DC Converter

Hidenori Maruta, Junya Sakemi, Akihiro Nakamura, Fujio Kurokawa, Hiroyuki Osuga


As energy saving becomes important for sustainable society, one of the important social problems
is to decrease the power consumption of the power converters such as those in renewable energy
systems and information systems. In these application fields, the superior digital control method of power
converter is needed. This paper presents a novel prediction based digitally controlled dc-dc converter. In
the presented method, the prediction based control is adopted as the feedforward control added to the
conventional P-I-D control as the feedback control. This prediction based control performs to control
dynamical properties of the system and it is realized by a neural network approach. This neural network
based control improves the transient response very effectively when the load is changed quickly. As a
result, the undershoot of output voltage and the overshoot of reactor current are suppressed effectively
as compared with the conventional one in the step change of load resistance. Both in simulations and
experiments, it is confirmed that the presented prediction based control technique is useful to realize
the superior digitally controlled method for the dc-dc converter.

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dc-dc converter, digital control, neural network, feedforward control

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