Iterative Nonlinear Model Predictive Control

A review

J.R. Cueli

Escuela de Ingenieros. University of Seville. Camino de los Descubrimientos, s/n. 41092, Seville, Spain jose.ramos-cueli@mariecurie.org

ABSTRACT. This article aims to present a compilation of the work done with Iterative Nonlinear Model Predictive Control (INMPC). Its main purpose is to control non linear processes, and it is applicable when the process is batch-type and an enough-accurate plant model is available. Additionally, it can be used to iteratively invert an arbitrary plant. Because any industrial process has a startup phase, the controller is also applicable to enhance the trajectories in this phase. This controller has some interesting convergence properties. In fact, it converges under mild assumptions, being the main one the necessity of starting at the same initial conditions every batch (or run). The use of predictive techniques permits the optimal resolution of the constrained control problem. However, the convergence property has only been established in the unconstrained case. It has a limited number of parameters, which may be easily tuned. Controller properties are illustrated with simple examples and finally, some applications are presented: a chemical batch and semibatch reactor and the startup phase of an industrial process - the preparation phase of olive oil.

KEYWORDS: Predictive control, nonlinear control, batch processes, iterative control

1. Introduction

In this communication, a new ...

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