A Condensed and Sparse QP Formulation for Predictive Control

The computational burden that Model Predictive Control (MPC) imposes depends to a large extent on the way the optimal control problem is formulated as an optimization problem. In this paper, the authors present a new formulation those results in a compact and sparse optimization problem to be solved at each sampling interval. The approach is based on a change of variables that leads to a block banded hessian when the horizon length is bigger than the controllability index of the plant.