Modeling techniques used in building HVAC control systems: A review
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Gm. Shafiullah | Gary Higgins | Tania Urmee | Zakia Afroz | G. Shafiullah | T. Urmee | Z. Afroz | G. Higgins
[1] Ian Watson,et al. A Case Study of Maintenance of a Commercially Fielded Case‐Based Reasoning System , 2001, Comput. Intell..
[2] Teuku Meurah Indra Mahlia,et al. Chillers energy consumption, energy savings and emission analysis in an institutional buildings , 2011 .
[3] Puqiang Zhang,et al. Data-driven method based on particle swarm optimization and k-nearest neighbor regression for estimating capacity of lithium-ion battery , 2014 .
[4] Bruce H. Krogh,et al. Parameter identifiability for multi-zone building models , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[5] Ruxu Du,et al. Model-based Fault Detection and Diagnosis of HVAC systems using Support Vector Machine method , 2007 .
[6] Andrew Kusiak,et al. Predictive modeling and optimization of a multi-zone HVAC system with data mining and firefly algorithms , 2015 .
[7] Dongliang Zhang,et al. A dynamic simplified model of radiant ceiling cooling integrated with underfloor ventilation system , 2016 .
[8] Joseph Andrew Clarke,et al. Primitive parts: an approach to air-conditioning component modelling , 1997 .
[9] Viorel Badescu,et al. Renewable energy for passive house heating: II. Model , 2003 .
[10] Xiao Li,et al. Recent advances in dynamic modeling of HVAC equipment. Part 1: Equipment modeling , 2014 .
[11] Xiao Li,et al. Dynamic modeling and self-optimizing operation of chilled water systems using extremum seeking control , 2013 .
[12] Mohcine Zouak,et al. A comparison of linear and neural network ARX models applied to a prediction of the indoor temperature of a building , 2004, Neural Computing & Applications.
[13] G. Mustafaraj,et al. Development of room temperature and relative humidity linear parametric models for an open office using BMS data , 2010 .
[14] Bryan P. Rasmussen,et al. A nonlinear reduced-order modeling method for dynamic two-phase flow heat exchanger simulations , 2016 .
[15] Per Fahlén,et al. Estimation of operative temperature in buildings using artificial neural networks , 2006 .
[16] Tianzhen Hong,et al. On Variations of Space-heating Energy Use in Office Buildings , 2013 .
[17] Moncef Krarti,et al. Development of a Predictive Optimal Controller for Thermal Energy Storage Systems , 1997 .
[18] Jongil Park,et al. Dynamic simulation of a single-effect ammonia–water absorption chiller , 2007 .
[19] A. Greene,et al. Principles of heating, ventilating and air conditioning , 1936 .
[20] Zong Woo Geem,et al. A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..
[21] Yaoyu Li,et al. Dynamic Modeling of Mechanical Draft Counter-Flow Wet Cooling Tower With Modelica , 2010 .
[22] Mohammad. Rasul,et al. Energy conservation measures in an institutional building in sub-tropical climate in Australia , 2010 .
[23] Petru-Daniel Morosan,et al. Building temperature regulation using a distributed model predictive control , 2010 .
[24] M. Zaheeruddin,et al. Dynamic simulation and analysis of a water chiller refrigeration system , 2005 .
[25] Radiša Jovanović,et al. Ensemble of various neural networks for prediction of heating energy consumption , 2015 .
[26] António E. Ruano,et al. A greenhouse climate multivariable predictive controller. , 2000 .
[27] Shrikant Pandey,et al. Artificial neural networks for predicting indoor temperature using roof passive cooling techniques in buildings in different climatic conditions , 2012, Appl. Soft Comput..
[28] Zhiwei Lian,et al. Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique , 2006 .
[29] Joseph C. Lam,et al. Regression analysis of high-rise fully air-conditioned office buildings , 1997 .
[30] Dominique Marchio,et al. Simplified model for indirect-contact evaporative cooling-tower behaviour , 2004 .
[31] Ye Yao,et al. A simple dynamic model of cooling coil unit , 2006 .
[32] Yong Zhang,et al. Advanced controller auto-tuning and its application in HVAC systems , 2000 .
[33] James E. Braun,et al. An Inverse Gray-Box Model for Transient Building Load Prediction , 2002 .
[34] Lihua Xie,et al. Development of cooling coil model for system control and optimization , 2002 .
[35] Burcin Becerik-Gerber,et al. An online learning approach for quantifying personalized thermal comfort via adaptive stochastic modeling , 2015 .
[36] H. Mirinejad,et al. A review of intelligent control techniques in HVAC systems , 2012, 2012 IEEE Energytech.
[37] Youn-Seop Lee,et al. The Study on Cooling Load Forecast of an Unit Building using Neural Networks , 2003 .
[38] Hao Huang,et al. Multi-zone temperature prediction in a commercial building using artificial neural network model , 2013, 2013 10th IEEE International Conference on Control and Automation (ICCA).
[39] Yoram Halevi,et al. Optimal reduced order models with delay , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.
[40] Jin Wen,et al. Review of building energy modeling for control and operation , 2014 .
[41] Darren Robinson,et al. A generalised stochastic model for the simulation of occupant presence , 2008 .
[42] V. M. Salokhe,et al. Modelling of tropical greenhouse temperature by auto regressive and neural network models , 2008 .
[43] Nabil Nassif,et al. Artificial Intelligent Approaches for Modeling and Optimizing HVAC Systems , 2016 .
[44] Julio Ariel Romero,et al. A simplified black-box model oriented to chilled water temperature control in a variable speed vapour compression system , 2011 .
[45] Zhang Lin,et al. Global optimization of absorption chiller system by genetic algorithm and neural network , 2002 .
[46] N. Ghaddar,et al. Study of solar regenerated membrane desiccant system to control humidity and decrease energy consumption in office spaces , 2015 .
[47] John Burnett,et al. Mechanistic model of centrifugal chillers for HVAC system dynamics simulation , 2000 .
[48] S. Fok,et al. Neural-based air-handling unit for indoor relative humidity and temperature control. , 2005 .
[49] Chi-man Jacob Yiu,et al. Statistical modelling and forecasting schemes for air-conditioning system , 2008 .
[50] Kazuyuki Kamimura,et al. Chiller condition monitoring using topological case-based modeling , 1996 .
[51] Li Lanlan,et al. Support vector regression and ant colony optimization for HVAC cooling load prediction , 2010, 2010 International Symposium on Computer, Communication, Control and Automation (3CA).
[52] Teresa Wu,et al. Decentralized operation strategies for an integrated building energy system using a memetic algorithm , 2012, Eur. J. Oper. Res..
[53] Manfred Morari,et al. Modeling and identification of a large multi-zone office building , 2011, 2011 IEEE International Conference on Control Applications (CCA).
[54] Feng Hong,et al. Energy optimal control of a residential space-conditioning system based on sensible heat transfer modeling , 2004 .
[55] Lei Chen,et al. A neural network-based multi-zone modelling approach for predictive control system design in commercial buildings , 2015 .
[56] Jonghun Kim,et al. Thermal management of LED lighting integrated with HVAC systems in office buildings , 2016 .
[57] S. Kabelac. The transient response of finned crossflow heat exchangers , 1989 .
[58] Li Li,et al. Dynamic Characteristics Modeling of a Heat Exchanger Using Neural Network , 2008, 2008 First International Conference on Intelligent Networks and Intelligent Systems.
[59] James E. Braun,et al. A comparison of moving-boundary and finite-volume formulations for transients in centrifugal chillers , 2008 .
[60] Bourhan Tashtoush,et al. Dynamic model of an HVAC system for control analysis , 2005 .
[61] Aun-Neow Poo,et al. Support vector regression model predictive control on a HVAC plant , 2007 .
[62] Guoliang Ding,et al. Transient modeling of an air-cooled chiller with economized compressor. Part I: Model development and validation , 2009 .
[63] Chang Chieh Hang,et al. Reduced order process modelling in self-tuning control , 1991, Autom..
[64] Andrew Kusiak,et al. Multi-objective optimization of HVAC system with an evolutionary computation algorithm , 2011 .
[65] Rajesh Kumar,et al. Energy analysis of a building using artificial neural network: A review , 2013 .
[66] Xiaoshu Lü. Modelling of heat and moisture transfer in buildings: I. Model program , 2002 .
[67] D.P. Filev,et al. An approach to online identification of Takagi-Sugeno fuzzy models , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[68] F. W. Yu,et al. Improved energy management of chiller systems by multivariate and data envelopment analyses , 2012 .
[69] Samuel Privara,et al. Predictive control oriented subspace identification based on building energy simulation tools , 2012, 2012 20th Mediterranean Conference on Control & Automation (MED).
[70] Derk J. Swider. A comparison of empirically based steady-state models for vapor-compression liquid chillers , 2003 .
[71] Rubiyah Yusof,et al. A novel optimization algorithm based on epsilon constraint-RBF neural network for tuning PID controller in decoupled HVAC system , 2016 .
[72] Vojislav Kecman,et al. Modelling of vapour-compression liquid chillers with neural networks , 2001 .
[73] Jlm Jan Hensen,et al. Overview of HVAC system simulation , 2010 .
[74] Andrew Kusiak,et al. Performance optimization of HVAC systems with computational intelligence algorithms , 2014 .
[75] Josh Wall,et al. Adaptive HVAC zone modeling for sustainable buildings , 2010 .
[76] D. Subbaram Naidu,et al. Advanced control strategies for heating, ventilation, air-conditioning, and refrigeration systems—An overview: Part I: Hard control , 2011 .
[77] Rajani K. Mudi,et al. Self-Tuning Fuzzy PI Controller and its Application to HVAC Systems , 2008 .
[78] Shengwei Wang,et al. Dynamic simulation of a building central chilling system and evaluation of EMCS on-line control strategies , 1998 .
[79] John W. Mitchell,et al. The Transient Response of Heat Exchangers Having an Infinite Capacitance Rate Fluid , 1970 .
[80] Carlos F. Pfeiffer,et al. Control of temperature and energy consumption in buildings - a review. , 2014 .
[81] Junya Nishiguchi,et al. Data-driven optimal control for building energy conservation , 2010, Proceedings of SICE Annual Conference 2010.
[82] Frédéric Magoulès,et al. Parallel Support Vector Machines Applied to the Prediction of Multiple Buildings Energy Consumption , 2010 .
[83] Fariborz Haghighat,et al. Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and Artificial Neural Network , 2010 .
[84] Luis C. Dias,et al. Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application , 2014 .
[85] Stéphane Grieu,et al. Low computational cost technique for predictive management of thermal comfort in non-residential buildings , 2014 .
[86] Xiao Chen,et al. A data-driven state-space model of indoor thermal sensation using occupant feedback for low-energy buildings , 2015 .
[87] Alireza Askarzadeh,et al. An enhanced bat algorithm approach for reducing electrical power consumption of air conditioning systems based on differential operator , 2016 .
[88] Andrew Kusiak,et al. Multi-objective optimization of the HVAC (heating, ventilation, and air conditioning) system performance , 2015 .
[89] Andrew Kusiak,et al. Modeling and optimization of HVAC energy consumption , 2010 .
[90] Dennis L. Loveday,et al. Stochastic modelling of temperatures for a full-scale occupied building zone subject to natural random influences , 1993 .
[91] Andrew Kusiak,et al. Minimization of energy consumption in HVAC systems with data-driven models and an interior-point method , 2014 .
[92] Jie Chen,et al. Prediction of room temperature and relative humidity by autoregressive linear and nonlinear neural n , 2011 .
[93] Gianfranco Rizzo,et al. The control of indoor thermal comfort conditions: introducing a fuzzy adaptive controller , 2004 .
[94] Xin Zhang,et al. A novel artificial bee colony algorithm for HVAC optimization problems , 2013 .
[95] Bertil Thomas,et al. Artificial neural network models for indoor temperature prediction: investigations in two buildings , 2006, Neural Computing and Applications.
[96] Jiangjiang Wang,et al. Robust cascade control system design for central airconditioning system , 2008, 2008 7th World Congress on Intelligent Control and Automation.
[97] Jin Woo Moon,et al. Comparative study of artificial intelligence-based building thermal control methods – Application of fuzzy, adaptive neuro-fuzzy inference system, and artificial neural network , 2011 .
[98] M. Hosoz,et al. Performance prediction of a cooling tower using artificial neural network , 2007 .
[99] Farrukh Nagi,et al. RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD , 2012 .
[100] Yan Lu,et al. A Hybrid Physics-Based and Data Driven Approach to Optimal Control of Building Cooling/Heating Systems , 2016, IEEE Transactions on Automation Science and Engineering.
[101] M. V. Frank,et al. Predictions of Energy Savings in HVAC Systems by Lumped Models (Preprint) , 2010 .
[102] Eiji Hihara,et al. Prediction of air coil performance under partially wet and totally wet cooling conditions using equivalent dry-bulb temperature method , 2002 .
[103] Jiangjiang Wang,et al. Hybrid CMAC-PID Controller in Heating Ventilating and Air-Conditioning System , 2007, 2007 International Conference on Mechatronics and Automation.
[104] Manfred Morari,et al. Use of model predictive control and weather forecasts for energy efficient building climate control , 2012 .
[105] Hao Huang,et al. A new zone temperature predictive modeling for energy saving in buildings , 2012 .
[106] Sean Danaher,et al. Application of an Artificial Neural Network for Modelling the Thermal Dynamics of a Building’s Space and its Heating System , 2002 .
[107] Prabir Barooah,et al. Identification of multi-zone building thermal interaction model from data , 2011, IEEE Conference on Decision and Control and European Control Conference.
[108] M. Fasiuddin,et al. HVAC system strategies for energy conservation in commercial buildings in Saudi Arabia , 2011 .
[109] V. Ismet Ugursal,et al. Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector , 2008 .
[110] António E. Ruano,et al. Neural networks based predictive control for thermal comfort and energy savings in public buildings , 2012 .
[111] Jiejin Cai,et al. Applying support vector machine to predict hourly cooling load in the building , 2009 .
[112] Leslie K. Norford,et al. Naturally ventilated and mixed-mode buildings—Part I: Thermal modeling , 2009 .
[113] Yan Chen,et al. DEVELOPMENT OF A SIMULATION PLATFORM BASED ON DYNAMIC MODELS FOR HVAC CONTROL ANALYSIS , 2014 .
[114] Jan Pieters,et al. Modelling Greenhouse Temperature by means of Auto Regressive Models , 2003 .
[115] V. I. Hanby,et al. A Robust Evolutionary Algorithm for HVAC Engineering Optimization , 2008 .
[116] Yong Chan Kim,et al. Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method , 2016 .
[117] Nursyarizal Mohd Nor,et al. A review on optimized control systems for building energy and comfort management of smart sustainable buildings , 2014 .
[118] Wai Lok Chan,et al. An automatic data acquisition system for on-line training of artificial neural network-based air handling unit modeling , 2005 .
[119] Bo Wahlberg,et al. Physics-based modeling and identification for HVAC systems? , 2013, 2013 European Control Conference (ECC).
[120] Lihua Xie,et al. A simplified modeling of cooling coils for control and optimization of HVAC systems , 2004 .
[121] V. Geros,et al. Modeling and predicting building's energy use with artificial neural networks: Methods and results , 2006 .
[122] Alberto Hernandez Neto,et al. Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption , 2008 .
[123] Jin Woo Moon,et al. Prediction Performance of an Artificial Neural Network Model for the Amount of Cooling Energy Consumption in Hotel Rooms , 2015 .
[124] Thananchai Leephakpreeda,et al. Grey prediction on indoor comfort temperature for HVAC systems , 2008, Expert Syst. Appl..
[125] Jing Chen,et al. State-space model for dynamic behavior of vapor compression liquid chiller , 2013 .
[126] Chang-Chieh Hang,et al. Robust identification of first-order plus dead-time model from step response , 1999 .
[127] Bryan P. Rasmussen,et al. Automated Multi-Zone Linear Parametric Black Box Modeling Approach for Building HVAC Systems , 2015, HRI 2015.
[128] Nabil Nassif,et al. Self-Tuning Dynamic Models of HVAC System Components , 2008 .
[129] Jiejin Cai,et al. Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks , 2009 .
[130] Viorel Badescu,et al. Renewable energy for passive house heating: Model of the active solar heating system , 2006 .
[131] Jing Zhao,et al. The analysis of energy consumption of a commercial building in Tianjin, China , 2009 .
[132] Ye Yao,et al. A review of recent developments and technological advancements of variable-air-volume (VAV) air-conditioning systems , 2016 .
[133] E. Stanley Lee,et al. Fuzzy adaptive networks in thermal comfort , 2006, Appl. Math. Lett..
[134] Li Lanlan,et al. A novel building cooling load prediction based on SVR and SAPSO , 2010, 2010 International Symposium on Computer, Communication, Control and Automation (3CA).
[135] G. J. Rios-Moreno,et al. Modelling temperature in intelligent buildings by means of autoregressive models , 2007 .
[136] Lei Jia,et al. Predictive functional control based on fuzzy T-S model for HVAC systems temperature control , 2007 .
[137] Farrokh Janabi-Sharifi,et al. Black-box modeling of residential HVAC system and comparison of gray-box and black-box modeling methods , 2015 .
[138] Martin Horn,et al. Temperature control for HVAC systems based on exact linearization and model predictive control , 2011, 2011 IEEE International Conference on Control Applications (CCA).
[139] Yutaka Iino,et al. Hybrid modeling with physical and JIT model for building thermal load prediction and optimal energy saving control , 2009, 2009 ICCAS-SICE.
[140] Christian Ghiaus,et al. Calculation of optimal thermal load of intermittently heated buildings , 2010 .
[141] A. Vehauc,et al. The effect of the choice of the enthalpy zero point on cooling tower design and packing data processing , 1992 .
[142] Jiangjiang Wang,et al. Analytical design of decoupling control for variable-air-volume air-conditioning system , 2008, 2008 IEEE Conference on Cybernetics and Intelligent Systems.
[143] Chunfeng Yang,et al. Utilizing artificial neural network to predict energy consumption and thermal comfort level: an indoor swimming pool case study , 2014 .
[144] B. D. Hunn,et al. Evaluation of strategies for controlling humidity in residences in humid climates , 1994 .
[145] Chun-Fa Zhang,et al. Research of Cascade Control with an Application to Central Air-Conditioning System , 2007, 2007 International Conference on Machine Learning and Cybernetics.
[146] Shengwei Wang,et al. A robust model predictive control strategy for improving the control performance of air-conditioning systems , 2009 .
[147] Frédéric Magoulès,et al. A review on the prediction of building energy consumption , 2012 .
[148] Francesco Borrelli,et al. Stochastic Model Predictive Control for Building HVAC Systems: Complexity and Conservatism , 2015, IEEE Transactions on Control Systems Technology.
[149] Raad Z. Homod,et al. Review on the HVAC System Modeling Types and the Shortcomings of Their Application , 2013 .
[150] Kamel Ghali,et al. Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm , 2009 .
[151] Farrokh Janabi-Sharifi,et al. Review of modeling methods for HVAC systems , 2014 .
[152] Arun Kumar,et al. A review on modeling and simulation of building energy systems , 2016 .
[153] Paul Kohlenbach,et al. A dynamic simulation model for transient absorption chiller performance. Part II: Numerical results and experimental verification , 2008 .
[154] António E. Ruano,et al. Prediction of building's temperature using neural networks models , 2006 .
[155] Paul Kohlenbach,et al. A dynamic simulation model for transient absorption chiller performance. Part I The model , 2008 .
[156] James E. Braun,et al. A general multi-agent control approach for building energy system optimization , 2016 .
[157] Ryohei Yokoyama,et al. Prediction of energy demands using neural network with model identification by global optimization , 2009 .
[158] Alessandro Beghi,et al. VAVAC systems modeling and simulation for FDD applications , 2011, 2011 9th IEEE International Conference on Control and Automation (ICCA).
[159] Zhiwei Lian,et al. Thermal analysis of cooling coils based on a dynamic model , 2004 .
[160] Henrik Madsen,et al. Models for describing the thermal characteristics of building components , 2008 .
[161] Gerardo Maria Mauro,et al. Artificial neural networks to predict energy performance and retrofit scenarios for any member of a building category: A novel approach , 2017 .
[162] Seyed Mohammad Ali Mohammadi,et al. A new mathematical dynamic model for HVAC system components based on Matlab/Simulink , 2012 .
[163] Chris P. Underwood,et al. HVAC Control Systems: Modelling, Analysis and Design , 1999 .
[164] Christian Inard,et al. Grey-box identification of air-handling unit elements , 2007 .
[165] Luis Pérez-Lombard,et al. A review on buildings energy consumption information , 2008 .
[166] Farrokh Janabi-Sharifi,et al. Theory and applications of HVAC control systems – A review of model predictive control (MPC) , 2014 .
[167] J. C. Kloppers,et al. The Lewis factor and its influence on the performance prediction of wet-cooling towers , 2005 .
[168] S. Gunn. Support Vector Machines for Classification and Regression , 1998 .
[169] Henrik Madsen,et al. Identification of the main thermal characteristics of building components using MATLAB , 2008 .
[170] Servet Soyguder,et al. Predicting of fan speed for energy saving in HVAC system based on adaptive network based fuzzy inference system , 2009, Expert Syst. Appl..
[171] M. P. Maiya,et al. Analysis of modified counter-flow cooling towers , 1995 .
[172] B. Dong,et al. Applying support vector machines to predict building energy consumption in tropical region , 2005 .
[173] V. Badescu,et al. Warm season cooling requirements for passive buildings in Southeastern Europe (Romania) , 2010 .
[174] Tao Lu,et al. Prediction of indoor temperature and relative humidity using neural network models: model comparison , 2009, Neural Computing and Applications.
[175] Zhongsheng Hou,et al. Lazy-Learning-Based Data-Driven Model-Free Adaptive Predictive Control for a Class of Discrete-Time Nonlinear Systems , 2017, IEEE Trans. Neural Networks Learn. Syst..
[176] Zhiwei Lian,et al. An Application of Support Vector Machines in Cooling Load Prediction , 2009, 2009 International Workshop on Intelligent Systems and Applications.
[177] Anastasios I. Dounis,et al. Advanced control systems engineering for energy and comfort management in a building environment--A review , 2009 .
[178] Gordon Lowry,et al. Modelling the passive thermal response of a building using sparse BMS data , 2004 .
[179] Frauke Oldewurtel,et al. Experimental analysis of model predictive control for an energy efficient building heating system , 2011 .
[180] Haralambos Sarimveis,et al. A Simulated Annealing Algorithm for Prioritized Multiobjective Optimization—Implementation in an Adaptive Model Predictive Control Configuration , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[181] M. Zaheer-uddin,et al. A VAV system model for simulation of energy management control functions: Off normal operation and duty cycling , 1994 .
[182] Zhenjun Ma,et al. Supervisory and Optimal Control of Building HVAC Systems: A Review , 2008 .
[183] B. J. Bailey,et al. Neural Network Models of the Greenhouse Climate , 1994 .
[184] Leopold,et al. Application of artificial neural network for predicting hourly indoor air temperature and relative humidity in modern building in humid region , 2016 .
[185] Thananchai Leephakpreeda,et al. Neural computing thermal comfort index for HVAC systems , 2005 .
[186] Tianzhen Hong,et al. Stochastic modeling of overtime occupancy and its application in building energy simulation and calibration , 2014, Building and Environment.
[187] Lukas Ferkl,et al. Model predictive control of a building heating system: The first experience , 2011 .
[188] Marcus M. Keane,et al. HEAT VENTILATION AND AIR CONDITIONING MODELLING FOR MODEL BASED FAULT DETECTION AND DIAGNOSIS , 2013 .
[189] Shengwei Wang,et al. Robust Model Predictive Control of VAV Air-Handling Units Concerning Uncertainties and Constraints , 2010 .
[190] Refrigerating. ASHRAE handbook and product directory /published by the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc , 1977 .
[191] Weiming Shen,et al. Inverse blackbox modeling of the heating and cooling load in office buildings , 2017 .
[192] Philippe Andre,et al. Simulation of a centralized cooling plant under different control strategies , 1997 .
[193] Pradeep Bansal,et al. Transient simulation of vapour-compression packaged liquid chillers , 2002 .
[194] Farrokh Janabi-Sharifi,et al. Gray-box modeling and validation of residential HVAC system for control system design , 2015 .
[195] D. Subbaram Naidu,et al. Advanced control strategies for HVAC&R systems—An overview: Part II: Soft and fusion control , 2011 .
[196] Shengwei Wang,et al. Multiple ARMAX modeling scheme for forecasting air conditioning system performance , 2007 .
[197] Guang-Yu Jin,et al. Cooling Coil Unit dynamic control of in HVAC system , 2011, 2011 6th IEEE Conference on Industrial Electronics and Applications.