Model predictive control is a receding horizon control policy in which a linear or quadratic program with linear constraints is solved on-line at each sampling instance. An algorithm is developed that allows quick computation of suboptimal control moves. The linear constraint set is approximated by an ellipsoid and a change of variables is performed so that a solution may be computed efficiently via bisection. The ellipsoid is rescaled on-line to reduce conservatism. This allows the implementation of model predictive control algorithms to large scale processes using simple control hardware.