On Economic Optimality of Model Predictive Control

Author

Ferramosca, Antonio ; Gonzalez, Adriana ; Limon, Daniel ; Bustos, German ; Godoy, Jose Luis ; Marchetti, Jacinto

Author_Institution

Inst. de Desarrollo Tecnol. para la Ind. Quim., Santa Fe, Argentina

Volume

12

Issue

7

fYear

2014

fDate

Oct. 2014

Firstpage

1234

Lastpage

1241

Abstract

Model Predictive Control (MPC) is the most used advanced control strategy in the industries, mainly due to its capability to fulfill economic objectives, taking into account a dynamic simplified model of the plant, constraints, and stability requirements. In the last years, several economic formulations of MPC have been presented, which get over the standard setpoint-tracking formulation. The goal of this work is to provide, by means of application to a highly nonlinear plant, a comparison of different strategies, focusing mainly on economic optimality, computational burden, and economic performance.

Keywords

predictive control; stability; MPC; computational burden; control strategy; dynamic simplified model; economic formulation; economic objectives; economic optimality; economic performance; model predictive control; nonlinear plant; stability requirement; standard setpoint-tracking formulation; Chemical reactors; Computational modeling; Economics; Inductors; Predictive control; Predictive models; Silicon compounds; Economics; Model Predictive Control; Real Time Optimization;

fLanguage

English

Journal_Title

Latin America Transactions, IEEE (Revista IEEE America Latina)

Publisher

ieee

ISSN

1548-0992

Type

jour

DOI

10.1109/TLA.2014.6948858

Filename

6948858