Sobre la Optimalidad Económica del Control Predictivo Basado en Modelo (On Economic Optimality of Model Predictive Control)

Antonio Ferramosca (ferramosca@santafe-conicet.gov.ar), Alejandro González (), Daniel Limón (), Germán Bustos (), José Luis Godoy (), Jacinto Marchetti ()


Instituto de Desarrollo Tecnológico para la Industria Química, CONICET
This paper appears in: Revista IEEE América Latina

Publication Date: Oct. 2014
Volume: 12,   Issue: 7 
ISSN: 1548-0992


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.

Index Terms:
Model Predictive Control, Economics, Real Time Optimization   


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