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

Författare

  • Per-Ola Larsson
  • Francesco Casella
  • Fredrik Magnusson
  • Joel Andersson
  • Moritz Diehl
  • Johan Åkesson

Summary, in English

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.

Publiceringsår

2013

Språk

Engelska

Sidor

346-351

Publikation/Tidskrift/Serie

IEEE Conference on Computer Aided Control System Design (CACSD), 2013

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Control Engineering

Conference name

IEEE Multi-conference on Systems and Control, 2013

Conference date

2013-08-27 - 2013-08-30

Conference place

Hyderabad, India

Status

Published

Projekt

  • Numerical and Symbolic Algorithms for Dynamic Optimization
  • LCCC

Forskningsgrupp

  • LCCC

ISBN/ISSN/Övrigt

  • ISBN: 9781479915644