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Journal of Control Science and Engineering
Volume 2017 (2017), Article ID 5636145, 15 pages
Research Article

Study of Error Propagation in the Transformations of Dynamic Thermal Models of Buildings

Univ Lyon, CNRS, INSA-Lyon, Université Claude Bernard Lyon 1, CETHIL UMR5008, 69621 Villeurbanne, France

Correspondence should be addressed to Loïc Raillon; rf.noyl-asni@1nolliar.ciol

Received 14 February 2017; Revised 14 June 2017; Accepted 28 June 2017; Published 6 September 2017

Academic Editor: Du Zhimin

Copyright © 2017 Loïc Raillon and Christian Ghiaus. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Dynamic behaviour of a system may be described by models with different forms: thermal (RC) networks, state-space representations, transfer functions, and ARX models. These models, which describe the same process, are used in the design, simulation, optimal predictive control, parameter identification, fault detection and diagnosis, and so on. Since more forms are available, it is interesting to know which one is the most suitable by estimating the sensitivity of the model to transform into a physical model, which is represented by a thermal network. A procedure for the study of error by Monte Carlo simulation and of factor prioritization is exemplified on a simple, but representative, thermal model of a building. The analysis of the propagation of errors and of the influence of the errors on the parameter estimation shows that the transformation from state-space representation to transfer function is more robust than the other way around. Therefore, if only one model is chosen, the state-space representation is preferable.