A framework for nonlinear model-predictive control using object-oriented modeling with a case study in power plant start-up

• Published in: 2013 IEEE Conference on Computer Aided Control System Design (CACSD) pp. 346 - 351
• Main Authors: Larsson, Per-Ola, Casella, Francesco, Magnusson, Fredrik, Andersson, Joel, Diehl, Moritz, Akesson, Johan
• Format: Conference Proceeding Book Chapter
• Language: English
• Published: IEEE 01.08.2013
• Subjects: Control Engineering; Electrical Engineering, Electronic Engineering, Information Engineering; Elektroteknik och elektronik; Engineering and Technology; Load modeling; Mathematical model; Numerical models; Object oriented modeling; Optimization; Reglerteknik; Stress; Teknik; Turbines
• ISBN: 9781479915644; 1479915645
• ISSN: 2165-3011
• DOI: 10.1109/CACSD.2013.6663487

In t his 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.