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Shortest-Prediction Horizon Nonlinear Model Predictive Control1
Journal article   Open access

Shortest-Prediction Horizon Nonlinear Model Predictive Control1

Masoud Soroush and Masoud Nikravesh
IFAC Proceedings Volumes, v 29(1), pp 5817-5822
Jun 1996
DOI: https://doi.org/10.1016/S1474-6670(17)58611-5
url
https://doi.org/10.1016/s1474-6670(17)58611-5View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze),  Open

Abstract

differential geometric methods input-output linearization model predictive control model reference control model-based control nonlinear control
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.

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