Analysis and Application of Advanced Control Strategies to a Heating Element Nonlinear Model

Turhan, Cihan; Simani, Silvio; Zajic, Ivan; Akkurt, Gülden Gökçen

doi:10.1088/1742-6596/783/1/012027

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…Moreover, this work illustrates the design and the implementation of different control schemes with application to a nonlinear TU dynamic module proposed by the same authors in [9]. Note also that the same authors presented some preliminary results in [23][24][25], but the analysis of the achievable properties and the robustness features of the proposed solutions with their reliability characteristics have been described in detail in this paper.…”

Section: Introductionmentioning

confidence: 92%

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

et al. 2017

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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.

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Section: Introductionmentioning

confidence: 92%

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

et al. 2017

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“…Moreover, this work illustrates the design and the implementation of different control schemes with application to a nonlinear TU dynamic module proposed by the same authors in [9]. Note also that the same authors presented some preliminary results in [23][24][25], but the analysis of the achievable properties, the robustness features of the proposed solutions with their reliability characteristics have been described in detail in this paper.…”

Section: Introductionmentioning

confidence: 92%

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

Turhan

Simani

Zajic

et al. 2016

Preprint

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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 analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application 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.

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“…. See, e.g., [3], [4], [6], [7], [8], [10], [11], [15], [16], [20], [25], [26], [27], [32], [36], [39], [44], [46], [49], [50], [52], [61], [64], [67], . .…”

Section: Introductionmentioning

confidence: 99%

Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

Abouaïssa

Hasan

Join

et al. 2017

2017 21st International Conference on System Theory, Control and Computing (ICSTCC)

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The model-based control of building heating systems for energy saving encounters severe physical, mathematical and calibration difficulties in the numerous attempts that has been published until now. This topic is addressed here via a new model-free control setting, where the need of any mathematical description disappears. Several convincing computer simulations are presented. Comparisons with classic PI controllers and flatness-based predictive control are provided.

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Analysis and Application of Advanced Control Strategies to a Heating Element Nonlinear Model

Cited by 5 publications

References 17 publications

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

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

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

Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

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Analysis and Application of Advanced Control Strategies to a Heating Element Nonlinear Model

Cited by 5 publications

References 17 publications

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

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

Performance Analysis of Data&ndash;Driven and Model&ndash;Based Control Strategies Applied to a Thermal Unit Model

Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

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