Improved online identification of switching converters using digital network analyzer techniques

Recent progress in the identification of switching power converters using an all-digital controller has granted network analyzer functionality to the control platform. In particular, the cross-correlation technique provides a nonparametric identification of a converterpsilas small-signal control-to-output frequency response. The literature shows the viability of this technique as well as a few improvements to the basic technique. This online network analyzer functionality allows new flexibility in the areas of online monitoring and adaptive control. In this paper, several improvements to the cross-correlation method of system identification are proposed which aim to further improve the accuracy of the frequency response identification, particularly at high frequencies near the desired closed-loop bandwidth. Additionally, an extension to the cross-correlation method is proposed which allows measurement of the control loop gain without ever opening the feedback loop. Thus, performance and stability margins may be evaluated while maintaining tight regulation of the output. Simulation and experimental results are shown to verify the proposed improvements.