Multirate Nonlinear Predictive Control

This paper introduces a new approach to reduce the computational load of nonlinear model based predictive controllers. The idea is based on dividing a long prediction horizon into only a few equidistant intervals with piecewise constant control signals. After solving a first dynamic optimization problem the prediction horizon is halved, keeping the second half of the solution fixed and doubling the sampling rate in the first half of the control horizon. Using these settings a second optimization is performed to improve the first acquired solution. This procedure is repeated until the applied control step has a reasonable sampling time. In this paper the multirate method is merged with the Quasi-Infinite Horizon Nonlinear Predictive Control scheme, based on augmenting the optimization problem with a terminal region condition and the objective function with a quadratic terminal cost term. Some illustrative simulation results are presented to show the improved stability and computational cost properties of the resulting control strategy without deteriorated quality of control.