Sampled-data modeling of switching regulators

The high-frequency capabilities of two switching regulator modeling techniques, state-space averaging and discrete modeling, are compared. A new linear, small-signal modeling technique, which combines the continuous form of state-space averaging with the accuracy of discrete modeling, is then developed. This new method, called sampled-data modeling, succeeds, where state-space averaging fails, in predicting the subharmonic instability in current-programmed regulators, and is shown to be of significant usefulness in the design of high-performance switching regulators.