Conference Contribution

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

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


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 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.


In 2013 IEEE Multi-Conference on Systems and Control, Hyderabad, India , August 2013.

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