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Energies 2017, 10(1), 67; doi:10.3390/en10010067

Performance Analysis of Data-Driven and Model-Based Control Strategies Applied to a Thermal Unit Model

1
Mechanical Engineering, Izmir Institute of Technology, Gulbahce Campus, Urla, 35430 Izmir, Turkey
2
Dipartimento di Ingegneria, Università degli Studi di Ferrara. Via Saragat 1E, 44122 Ferrara (FE), Italy
3
Control Theory and Applications Centre, Coventry University, Coventry CV1 5FB, UK
4
Energy Engineering Program, Izmir Institute of Technology, Gulbahce Campus, Urla, 35430 Izmir, Turkey
*
Author to whom correspondence should be addressed.
Academic Editor: Lei Feng
Received: 27 November 2016 / Revised: 8 December 2016 / Accepted: 24 December 2016 / Published: 7 January 2017
(This article belongs to the Special Issue Energy Management Control)
View Full-Text   |   Download PDF [563 KB, uploaded 7 January 2017]   |  

Abstract

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model 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. View Full-Text
Keywords: modelling and simulation for control; advanced control design; model-based and data-driven approaches; artificial intelligence; thermal unit nonlinear system modelling and simulation for control; advanced control design; model-based and data-driven approaches; artificial intelligence; thermal unit nonlinear system
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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. (CC BY 4.0).

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MDPI and ACS Style

Turhan, C.; Simani, S.; Zajic, I.; Gokcen Akkurt, G. Performance Analysis of Data-Driven and Model-Based Control Strategies Applied to a Thermal Unit Model. Energies 2017, 10, 67.

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