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 …

Abstract 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 sub-optimal 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 …