Efficient quadratic programming algorithms for model predictive control

The model predictive control problem for process systems with linear constraints can be expressed as a quadratic program. In this paper, different algorithms to solve linear quadratic model predictive control problems are presented and compared from the view point of computation time. A modification of the existing algorithms, referred as initially unconstrained method, is also proposed and found to further reduce the computation time.