Publication:
RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD

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dc.citedby74
dc.contributor.authorHomod R.Z.en_US
dc.contributor.authorMohamed Sahari K.S.en_US
dc.contributor.authorAlmurib H.A.F.en_US
dc.contributor.authorNagi F.H.en_US
dc.contributor.authorid36994633500en_US
dc.contributor.authorid57218170038en_US
dc.contributor.authorid35305238400en_US
dc.contributor.authorid56272534200en_US
dc.date.accessioned2023-12-28T06:30:22Z
dc.date.available2023-12-28T06:30:22Z
dc.date.issued2012
dc.description.abstractThis work presents a hybrid model to be used for effectively controlling indoor thermal comfort in a heating, ventilating and air conditioning (HVAC) system. The first modeling part is related to the building structure and its fixture. Since building models contain many nonlinearities and have large thermal inertia and high delay time, empirical calculations based on the residential load factor (RLF) is adopted to represent the model. The second part is associated with the indoor thermal comfort itself. To evaluate indoor thermal comfort situations, predicted mean vote (PMV) and predicted percentage of dissatisfaction (PPD) indicators were used. This modeling part is represented as a fuzzy PMV/PPD model which is regarded as a white-box model. This modeling is achieved using a Takagi-Sugeno (TS) fuzzy model and tuned by Gauss-Newton method for nonlinear regression (GNMNR) algorithm. The main reason for combining the two models is to obtain a proper reference signal for the HVAC system. Unlike the widely used temperature reference signal, the proposed reference signal resulting from this work is closely related to thermal sensation comfort; Temperature is one of the factors affecting the thermal comfort but is not the main measure, and therefore, it is insignificant to control thermal comfort when the temperature is used as the reference for the HVAC system. The overall proposed model is tested on a wide range of parameter variation. The corresponding results show that a good modeling capability is achieved without employing any complicated optimization procedures for structure identification with the TS model. � 2011 Elsevier Ltd.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.buildenv.2011.09.012
dc.identifier.epage153
dc.identifier.issue1
dc.identifier.scopus2-s2.0-80054107865
dc.identifier.spage141
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-80054107865&doi=10.1016%2fj.buildenv.2011.09.012&partnerID=40&md5=d9316bb722641cb2026fd5a9e0c74be5
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29527
dc.identifier.volume49
dc.pagecount12
dc.sourceScopus
dc.sourcetitleBuilding and Environment
dc.subjectBuilding model
dc.subjectEnergy control
dc.subjectHVAC
dc.subjectPMV/PPD
dc.subjectRLF method
dc.subjectThermal comfort
dc.subjectAir conditioning
dc.subjectIdentification (control systems)
dc.subjectNewton-Raphson method
dc.subjectPower control
dc.subjectSignal processing
dc.subjectStructural optimization
dc.subjectBuilding model
dc.subjectBuilding structure
dc.subjectDelay Time
dc.subjectEmpirical calculations
dc.subjectGauss-Newton methods
dc.subjectHVAC
dc.subjectHVAC system
dc.subjectHybrid model
dc.subjectIndoor thermal comfort
dc.subjectModeling capabilities
dc.subjectNon-linear regression
dc.subjectOptimization procedures
dc.subjectParameter variation
dc.subjectPMV/PPD
dc.subjectPredicted mean vote
dc.subjectReference signals
dc.subjectResidential load factors
dc.subjectRLF method
dc.subjectStructure identification
dc.subjectT S models
dc.subjectT-S fuzzy models
dc.subjectTakagi-sugeno fuzzy models
dc.subjectTemperature reference
dc.subjectThermal inertia
dc.subjectThermal sensations
dc.subjectWhite-box models
dc.subjectair conditioning
dc.subjectarchitectural design
dc.subjectfuzzy mathematics
dc.subjectGaussian method
dc.subjectindoor air
dc.subjectoptimization
dc.subjectThermal comfort
dc.titleRLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPDen_US
dc.typeArticleen_US
dspace.entity.typePublication
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