Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/6269
Title: Performance analysis of data-driven and model-based control strategies applied to a thermal unit model
Authors: Turhan, Cihan
Simani, Silvio
Zajic, Ivan
Gökçen Akkurt, Gülden
Keywords: Artificial intelligence
Advanced control design
Thermal unit nonlinear system
Issue Date: 2017
Publisher: MDPI Multidisciplinary Digital Publishing Institute
Source: Turhan, C., Simani, S., Zajic, I., and Gökçen Akkurt, G. (2017). Performance analysis of data-driven and model-based control strategies applied to a thermal unit model. Energies, 10(1). doi:10.3390/en10010067
Abstract: The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinearmodel of a thermal unit. A data-driven grey-box identification approach provided the physically-meaningful nonlinear continuous-time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important, since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte Carlo (MC) analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application of the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model-based and data-driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.
URI: http://doi.org/10.3390/en10010067
http://hdl.handle.net/11147/6269
ISSN: 1996-1073
1996-1073
Appears in Collections:Energy Systems Engineering / Enerji Sistemleri Mühendisliği
Mechanical Engineering / Makina Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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