Abstract
This paper presents the outcome of a project aiming at the development of a building simulator designed using Matlab® and Simulink® environments. The objective was to be able to test different control algorithms using the hardware-in-the-loop principle in a fast, flexible and effective way. The developed software allows one to simulate continuous dynamics of particular parameters in various time horizons, including a whole year simulation. The simulator has been used to test one of the model predictive control algorithms, implemented in the Node-RED environment and installed on the Beaglebone Black board.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andersen, K.K., Madsen, H., Hansen, L.H.: Modelling the heat dynamics of a building using stochastic differential equations. Energy Build. 31(1), 13–24 (2000). https://doi.org/10.1016/S0378-7788(98)00069-3
Lawrynczuk, M.: Accuracy and computational efficiency of suboptimal nonlinear predictive control based on neural models. Appl. Soft Comput. 11(2), 2202–2215 (2011). https://doi.org/10.1016/j.asoc.2010.07.021
Lawrynczuk, M.: Suboptimal nonlinear predictive control based on multivariable neural Hammerstein models. Appl. Intell. 32(2, SI), 173–192 (2010). https://doi.org/10.1007/s10489-010-0211-x
Jabłoński, K., Grychowski, T.: Fuzzy inference system for the assessment of indoor environmental quality in a room. Indoor Built Environ. 27(10), 1415–1430 (2018). https://doi.org/10.1177/1420326X17728097
Hudson, G., Underwood, C.: A simple building modelling procedure for MATLAB/SIMULINK. In: Proceedings of the International Building Performance and Simulation Conference, Kyoto Japan, vol. 2, pp. 777–783. Citeseer (1999)
Perera, D., Winkler, D., Skeie, N.O.: Multi-floor building heating models in MATLAB and Modelica environments. Appl. Energy 171, 46–57 (2016). https://doi.org/10.1016/j.apenergy.2016.02.143
Freitas, S., Catita, C., Redweik, P., Brito, M.: Modelling solar potential in the urban environment: State-of-the-art review. Renew. Sustain. Energy Rev. 41, 915–931 (2015). https://doi.org/10.1016/j.rser.2014.08.060
Lawrynczuk, M.: Nonlinear state-space predictive control with on-line linearisation and state estimation. Int. J. Appl. Math. Comput. Sci. 25(4), 833–847 (2015). https://doi.org/10.1515/amcs-2015-0060
Söderström, T., Stoica, P.: System Identification. Prentice Hall International, Inc., New York (1989)
Bismor, D.: Extension of LMS stability condition over a wide set of signals. Int. J. Adapt. Control Signal Process. 29(5), 653–670 (2015). https://doi.org/10.1002/acs.2500
Bismor, D., Pawelczyk, M.: Stability conditions for the leaky LMS algorithm based on control theory analysis. Arch. Acoust. 41(4), 731–740 (2016). https://doi.org/10.1515/aoa-2016-0070
Node-red (2019). https://nodered.org/
N-API documentation (2019). https://nodejs.org/api/n-api.html
Acknowledgment
The work described in this paper is within the project “Synergiczny system automatyki budynkowej zintegrowany z układami optymalizacji komfortu i klimatu w budynkach—SSAB”, which is co-sponsored by WND-RPSL.01.02.00-24-0853/17-001, Regional Operating Program for Silesian Voivodship for years 2014–2020.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Bismor, D., Jabłoński, K., Grychowski, T., Nas, S. (2020). Hardware-In-the-Loop Simulations of a GPC-Based Controller in Different Types of Buildings Using Node-RED. In: Bartoszewicz, A., Kabziński, J., Kacprzyk, J. (eds) Advanced, Contemporary Control. Advances in Intelligent Systems and Computing, vol 1196. Springer, Cham. https://doi.org/10.1007/978-3-030-50936-1_85
Download citation
DOI: https://doi.org/10.1007/978-3-030-50936-1_85
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-50935-4
Online ISBN: 978-3-030-50936-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)