A computationally attractive nonlinear predictive control scheme with guaranteed stability for stable systems

We introduce in this paper a nonlinear model predictive control scheme for open-loop stable systems subject to input and state constraints. Closed-loop stability is guaranteed by an appropriate choice of the finite prediction horizon, independent of the specification of the desired control performance. In addition, this control scheme is likely to allow ʹreal timeʹ implementation, because of its computational attractiveness. The theoretical results are demonstrated and discussed with a CSTR control application.