A New Prediction Based Digital Control for DC-DC Converter

Abstract

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

Keywords

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

References

1. “Energy Management And Conservation Program (Fiscal Year 2009)”, U.S. Environmental Protection Agency, Dec. 2009.
2. “FY 2008 Annual Energy Report”, Agency for Natural Resources and Energy, Ministry of Economy, Trade and Industry, Japan, Aug. 2009.
3. K. Kant, ”Toward a Science of Power Management”, IEEE Computer, vol. 42, no. 9, pp. 99-101, Sep. 2009.
4. J. Xiao, A. V. Peterchev and S. R. Sanders, ”Architecture and IC implementation of a digital VRM controller”, IEEE PESC Record, pp. 38-47, June 2001.
5. L. Guo, J. Y. Hung and R. M. Nelms, ”PID controller modifications to improve steady-state– performance of digital controllers for buck and boost converters”, Proc. of Annual IEEE Applied Power Electronics Conference, no. 9.3, pp. 381-388, March 2002.
6. Q. M. Li, ”A low-cost configurable PWM controller using programmable system-on-chip”, IEEE PESC Record, pp. 1169-1174, June 2003.
7. F. Kurokawa and W. Okamoto, ”Improvement of dynamic characteristics of digitally controlled switching power converter”, Proc. IEEE & IEEJ Power Conversion Conference, vol. 4, no.1, pp. 1147- 1153, April 2007.
8. H. Fujimoto and Y. Hori, ”Advanced digital motion control based on multirate sampling control”, Proc. IFAC Triennial World Congress, pp. 1603-1608, July 2002.

9. F. Kurokawa and S. Sukita, ”A new model control dc- dc converter to improve dynamic characteristics”, Proc. IEEE International Conference on Power Electronics and Drive Systems, pp. 763-767, Nov. 2007.
10. T. Hastie, R. Tibshirani and J. H. Friedman, The elements of statistical learning: data mining, inference, and prediction, Springer, 2001.
11. O. A. Kossov, ”Comparative analysis of chopper voltage regulators with LC filter,” IEEE Trans. Magnetics, Vol. MAG-4, no.4, pp. 712-715, 1968.
12. H. Matsuo and K. Harada, ”Characteristics of dc-dc converter in the discontinuous mode of the reactor current”, Trans. IEICE of Japan, vol. J61-C, no.1, pp. 33-40, 1978.