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BRCM Matlab Toolbox: Model Generation for Model Predictive Building Control


D. Sturzenegger, D. Gyalistras, V. Semeraro, M. Morari, R. S. Smith

American Control Conference, Portland, pp. 1063-1069

Model predictive control (MPC) is a promising alternative in building control with the potential to improve energy efficiency and comfort and to enable demand response capabilities. Creating an accurate building model that is simple enough to allow the resulting MPC problem to be tractable is a challenging but crucial task in the control development. %In the research project OptiControl, MPC was successfully applied to control a whole office building for multiple months. Developing a model of the building suitable for MPC was by far the most challenging task. In this paper we introduce the Building Resistance-Capacitance Modeling (BRCM) Matlab Toolbox that facilitates the physical modeling of buildings for MPC. The Toolbox provides a means for the fast generation of (bi-)linear resistance-capacitance type models from basic geometry, construction and building systems data. Moreover, it supports the generation of the corresponding potentially time-varying costs and constraints. The Toolbox is based on previously validated modeling principles. In a case study a BRCM model was automatically generated from an EP input data file and its predictive capabilities were compared to the EP model. The Toolbox itself, the details of the modeling and the documentation can be found at


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% Autogenerated BibTeX entry
@InProceedings { StuEtal:2014:IFA_4568,
    author={D. Sturzenegger and D. Gyalistras and V. Semeraro and M. Morari and R.
	  S. Smith},
    title={{BRCM Matlab Toolbox: Model Generation for Model Predictive
	  Building Control}},
    booktitle={American Control Conference},
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