Optimization-based strategies for the operation of low-density polyethylene tubular reactors: nonlinear model predictive control


Abstract:

In this work, we present a general nonlinear model predictive control (NMPC) framework for low-density polyethylene (LDPE) tubular reactors. The framework is based on a first-principles dynamic model able to capture complex phenomena arising in these units. We first demonstrate the potential of using NMPC to simultaneously regulate and optimize the process economics in the presence of persistent disturbances such as fouling. We then couple the NMPC controller with a compatible moving horizon estimator (MHE) to provide output feedback. Finally, we discuss computational limitations arising in this framework and make use of recently proposed advanced-step MHE and NMPC strategies to provide nearly instantaneous feedback. © 2009 Elsevier Ltd. All rights reserved.

Año de publicación:

2009

Keywords:

  • MHE
  • nonlinear programming
  • Large-scale
  • NMPC
  • fouling
  • Polyethylene
  • ECONOMICS

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Ingeniería química
  • Optimización matemática

Áreas temáticas de Dewey:

  • Física aplicada
  • Dirección general
  • Programación informática, programas, datos, seguridad
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 9: Industria, innovación e infraestructura
  • ODS 12: Producción y consumo responsables
  • ODS 8: Trabajo decente y crecimiento económico
Procesado con IAProcesado con IA