Advanced

A Framework for Nonlinear Model-Predictive Control Using Object-Oriented Modeling with a Case Study in Power Plant Start-Up

Larsson, Per-Ola LU ; Casella, Francesco; Magnusson, Fredrik LU ; Andersson, Joel; Diehl, Moritz and Åkesson, Johan LU (2013) IEEE Multi-conference on Systems and Control, 2013 In IEEE Conference on Computer Aided Control System Design (CACSD), 2013 p.346-351
Abstract
In this paper, nonlinear model predictive control (NMPC) is applied to the start-up of a combined-cycle power plant. An object-oriented first-principle model library expressed in the high-level language Modelica has been written for the plant and used to set up the simulation and optimization models. The NMPC optimization problems are both encoded, using a high-level notation, and solved in the open-source framework JModelica.org. The results demonstrate the effectiveness of the framework and its high-level description. It bridges the gap between an intuitive physical modeling format and state of the art numerical optimization algorithms. Promising closed-loop control results are shown for plant start-up when the NMPC model contains... (More)
In this paper, nonlinear model predictive control (NMPC) is applied to the start-up of a combined-cycle power plant. An object-oriented first-principle model library expressed in the high-level language Modelica has been written for the plant and used to set up the simulation and optimization models. The NMPC optimization problems are both encoded, using a high-level notation, and solved in the open-source framework JModelica.org. The results demonstrate the effectiveness of the framework and its high-level description. It bridges the gap between an intuitive physical modeling format and state of the art numerical optimization algorithms. Promising closed-loop control results are shown for plant start-up when the NMPC model contains parametric errors and the simulation model, corresponding to the real plant, is subject to disturbances. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
IEEE Conference on Computer Aided Control System Design (CACSD), 2013
pages
346 - 351
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE Multi-conference on Systems and Control, 2013
external identifiers
  • Scopus:84893692239
ISBN
9781479915644
DOI
10.1109/CACSD.2013.6663487
project
LCCC
collocation
language
English
LU publication?
yes
id
f420a704-aee1-42cc-bb68-743e77efebed (old id 3972829)
date added to LUP
2013-08-22 11:51:59
date last changed
2016-10-13 04:37:32
@misc{f420a704-aee1-42cc-bb68-743e77efebed,
  abstract     = {In this paper, nonlinear model predictive control (NMPC) is applied to the start-up of a combined-cycle power plant. An object-oriented first-principle model library expressed in the high-level language Modelica has been written for the plant and used to set up the simulation and optimization models. The NMPC optimization problems are both encoded, using a high-level notation, and solved in the open-source framework JModelica.org. The results demonstrate the effectiveness of the framework and its high-level description. It bridges the gap between an intuitive physical modeling format and state of the art numerical optimization algorithms. Promising closed-loop control results are shown for plant start-up when the NMPC model contains parametric errors and the simulation model, corresponding to the real plant, is subject to disturbances.},
  author       = {Larsson, Per-Ola and Casella, Francesco and Magnusson, Fredrik and Andersson, Joel and Diehl, Moritz and Åkesson, Johan},
  isbn         = {9781479915644},
  language     = {eng},
  pages        = {346--351},
  publisher    = {ARRAY(0x998e668)},
  series       = {IEEE Conference on Computer Aided Control System Design (CACSD), 2013},
  title        = {A Framework for Nonlinear Model-Predictive Control Using Object-Oriented Modeling with a Case Study in Power Plant Start-Up},
  url          = {http://dx.doi.org/10.1109/CACSD.2013.6663487},
  year         = {2013},
}