Shortest-Prediction Horizon Nonlinear Model Predictive Control

Abstract

This article presents a continuous-time formulation of model predictive control. This formulation allows (i) to establish the connections between model predictive control and input-output linearizing control methods and (ii) to address the problems of constraint handling and windup in input-output linearizing control methods. Model predictive control laws with the shortest possible prediction horizon are derived for constrained nonlinear processes with deadtime. They have explicit analytical form, and thus their implementation does not require on-line optimization. Furthermore, in the absence of constraints, they are input-output linearizing.