Article | Proceedings of the 10<sup>th</sup> International Modelica Conference; March 10-12; 2014; Lund; Sweden | Setting up a framework for model predictive control with moving horizon state estimation using JModelica Linköping University Electronic Press Conference Proceedings
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Title:
Setting up a framework for model predictive control with moving horizon state estimation using JModelica
Author:
Mats Vande Cavey: KU Leuven, Department of Mechanical Engineering, Leuven, Belgium Roel De Coninck: KU Leuven, Department of Mechanical Engineering, Leuven, Belgium/3E nv., Brussels, Belgium Lieve Helsen: KU Leuven, Department of Mechanical Engineering, Leuven, Belgium
DOI:
10.3384/ecp140961295
Download:
Full text (pdf)
Year:
2014
Conference:
Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden
Issue:
096
Article no.:
138
Pages:
1295-1303
No. of pages:
9
Publication type:
Abstract and Fulltext
Published:
2014-03-10
ISBN:
978-91-7519-380-9
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet

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Optimal control using Modelica models has promising opportunities with the development of JModelica. A model predictive control framework for optimally controlling a floor heated building heated by a heat pump is proposed. The control inputs are applied to virtual building emulator model with a limited amount of measurements. State estimation is implemented using a moving horizon estimation to reinitialize the states of the controller model in every timestep. To use the moving horizon estimation; the implementation of the Modelica model is altered. A stochastic input is declared at the controller model state equations to represent the process noise (model error). The state estimation significantly improves the output matching between emulator and controller model. The JModelica optimization framework proves to be satisfactory for the limited size virtual case. Future work will be able to build on this framework to handle different models and prediction error.

Keywords: Model Predictive Control; Moving Horizon Estimation; State estimation; JModelica; Modelica

Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden

Author:
Mats Vande Cavey, Roel De Coninck, Lieve Helsen
Title:
Setting up a framework for model predictive control with moving horizon state estimation using JModelica
DOI:
http://dx.doi.org/10.3384/ecp140961295
References:

[1] R. De Coninck, F. Magnusson, J. Åkesson, L. Helsen, Grey-box Building Models for Model Order Reduction and Control, accepted for oral presentation at 10th International Modelica Conference, Lund, Sweden, 2014.

[2] J. Andersson, J. ° Akesson, F. Casella, and M. Diehl, “Integration of CasADi and JModelica. org,” in 8th International Modelica Conference, Dresden, Germany 2011.

[3] E. Haseltine, J. Rawlings, Critical Evaluation of Extended Kalman Filtering and Moving-Horizon Estimation, Industrial & Engineering Chemistry Research 2005 44 (8), pp. 2451-2460, 2005.

[4] R. De Coninck, R. Baetens, D. Saelens, A. Woyte, L. Helsen, a Rule-based demandside management of domestic hot water production with heat pumps in zero energy neighbourhoods, Journal of Building Performance Simulation, 2013.

[5] Niels Rode Kristensen, Henrik Madsen, Sten Bay Jørgensen, Parameter estimation in stochastic grey-box models, Automatica, Volume 40, Issue 2, pp. 225-237, February 2004.

[6] R. De Coninck, L. Helsen, A tool chain for model based predictive control of buildings based on grey-box models, Intelligent Building Operations location:Boulder, Colorado, USA, 2013.

[7] C. Verelst, Model Predictive Control of Ground Coupled Heat Pump Systems in Office Buildings, Leuven, Belgium, Ph.D. dissertation, Department of Mechanical Engineering, 2012, p 73.

Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden

Author:
Mats Vande Cavey, Roel De Coninck, Lieve Helsen
Title:
Setting up a framework for model predictive control with moving horizon state estimation using JModelica
DOI:
https://doi.org10.3384/ecp140961295
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