  We consider the problem of controlling switched-mode power converters using
model predictive control. Model predictive control requires solving
optimization problems in real time, limiting its application to systems with
small numbers of switches and a short horizon. We propose a technique for using
off-line computation to approximate the model predictive controller. This is
done by dividing the planning horizon into two segments, and using a quadratic
function to approximate the optimal cost over the second segment. The
approximate model predictive algorithm minimizes the true cost over the first
segment, and the approximate cost over the second segment, allowing the user to
adjust the computational requirements by changing the length of the first
segment. We conclude with two simulated examples.
