Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart Space
Researchers have reached a consensus on the thermal discomfort known as the major cause of sick building syndrome, which hurts people’s health and working efficiency greatly. As a result, the thermal environment satisfaction is important and thus many studies have been dedicated to thermal...
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doaj-69b989de0ff24965aad404bbde3479ed2020-11-25T02:32:03ZengMDPI AGApplied Sciences2076-34172018-06-0187103110.3390/app8071031app8071031Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart SpaceLei Hang0Do-Hyeun Kim1Department of Computer Engineering, Jeju National University, Jeju 63243, KoreaDepartment of Computer Engineering, Jeju National University, Jeju 63243, KoreaResearchers have reached a consensus on the thermal discomfort known as the major cause of sick building syndrome, which hurts people’s health and working efficiency greatly. As a result, the thermal environment satisfaction is important and thus many studies have been dedicated to thermal comfort over the past few decades. Predicted Mean Vote (PMV) is one of the globally used standards to express users’ comfort satisfaction with the given thermal moderate environments. It has been widely used in most of the Heating, Ventilation and Air Conditioning (HVAC) systems to maintain this standard of thermal comfort for occupants of buildings. However, the PMV model is developed on indoor experimental data without taking into account conditions of outdoor space, which greatly affects the performance of the existing HVAC systems and varies with the seasons. In this paper, an enhanced Model-based Predictive Control practical system for maintaining the indoor thermal comfort is demonstrated, including a multiple linear regression predictive model and an innovative fuzzy controller considering both the PMV index and the outdoor environment conditions. To verify the usability of the designed system, an Internet of Things (IoT) smart space prototype was chosen and experimentally tested in a building in Jeju, Korea. Moreover, thermal comfort regulation performances using the proposed approach have been compared with the existing one. The results of our work indicate that the proposed solution is capable of optimizing the thermal comfort condition according to seasonality and outperforms the conventional approaches in different performance indexes.http://www.mdpi.com/2076-3417/8/7/1031Internet of ThingsPMVMPCfuzzy controlthermal comfortHVACsmart space |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lei Hang Do-Hyeun Kim |
spellingShingle |
Lei Hang Do-Hyeun Kim Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart Space Applied Sciences Internet of Things PMV MPC fuzzy control thermal comfort HVAC smart space |
author_facet |
Lei Hang Do-Hyeun Kim |
author_sort |
Lei Hang |
title |
Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart Space |
title_short |
Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart Space |
title_full |
Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart Space |
title_fullStr |
Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart Space |
title_full_unstemmed |
Enhanced Model-Based Predictive Control System Based on Fuzzy Logic for Maintaining Thermal Comfort in IoT Smart Space |
title_sort |
enhanced model-based predictive control system based on fuzzy logic for maintaining thermal comfort in iot smart space |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2018-06-01 |
description |
Researchers have reached a consensus on the thermal discomfort known as the major cause of sick building syndrome, which hurts people’s health and working efficiency greatly. As a result, the thermal environment satisfaction is important and thus many studies have been dedicated to thermal comfort over the past few decades. Predicted Mean Vote (PMV) is one of the globally used standards to express users’ comfort satisfaction with the given thermal moderate environments. It has been widely used in most of the Heating, Ventilation and Air Conditioning (HVAC) systems to maintain this standard of thermal comfort for occupants of buildings. However, the PMV model is developed on indoor experimental data without taking into account conditions of outdoor space, which greatly affects the performance of the existing HVAC systems and varies with the seasons. In this paper, an enhanced Model-based Predictive Control practical system for maintaining the indoor thermal comfort is demonstrated, including a multiple linear regression predictive model and an innovative fuzzy controller considering both the PMV index and the outdoor environment conditions. To verify the usability of the designed system, an Internet of Things (IoT) smart space prototype was chosen and experimentally tested in a building in Jeju, Korea. Moreover, thermal comfort regulation performances using the proposed approach have been compared with the existing one. The results of our work indicate that the proposed solution is capable of optimizing the thermal comfort condition according to seasonality and outperforms the conventional approaches in different performance indexes. |
topic |
Internet of Things PMV MPC fuzzy control thermal comfort HVAC smart space |
url |
http://www.mdpi.com/2076-3417/8/7/1031 |
work_keys_str_mv |
AT leihang enhancedmodelbasedpredictivecontrolsystembasedonfuzzylogicformaintainingthermalcomfortiniotsmartspace AT dohyeunkim enhancedmodelbasedpredictivecontrolsystembasedonfuzzylogicformaintainingthermalcomfortiniotsmartspace |
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