Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2017 | OriginalPaper | Chapter

1. Introduction

Authors : Ye Yao, Yuebin Yu

Published in: Modeling and Control in Air-conditioning Systems

Publisher: Springer Berlin Heidelberg

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

With the development of economy and growth of people’s living standards, air-conditioning systems are increasingly popular for the improvement of thermal environment indoors, which results in ever-increasing energy consumption of buildings.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter Component Modeling with State-Space Method
Literature
1.
US Energy Information Administration (EIA).: Electric Power Monthly, Table 5.1, 11 March 2011
2.
US Department of Energy (DOE).: 2010 Buildings Energy Data Book, Sections 2.1.5 and 3.1.4 (2011)
3.
Building energy conservation research center of Tsinghua University, Annual Report on China Building Energy Efficiency (2013)
4.
Tsinghua university architecture technology science. DeST User Manual (2004)
5.
Park, C.: HVACSIM+ User’s Guide Update. National Institute of Standards and Technology (2008)
6.
Dols, W.S., Walton, G.N.: CONTAMW 2.0 User Manual. National Institute of Standards and Technology (2002)
7.
ASHRAE.: ASHRAE Handbook—Fundamentals. Atlanta (USA), GA (2009)
8.
Sami, S.M., Duong, T., Mercadier, Y., Galanis, N.: Prediction of the transient response of heat pumps. ASHRAE Trans. 93, 471–478 (1987)
9.
Sami, S.M., Comeau, M.A.: Development of a simulation model for predicting dynamic behavior of heat pumps with non-azeotropic refrigerant mixtures. Int. J. Energy Res. 16(4), 443–450 (1992)
10.
Sami, S.M., Dahmani, A.: Numerical prediction of dynamic performance of vapor compression heat pump using new HFC alternatives to HCFC-22. J. Appl. Thermal Eng. 16(8/9), 691–705 (1996)CrossRef
11.
Lei, Z., Zaheeruddin, M.: Dynamic simulation and analysis of a water chiller refrigeration system. Appl. Therm. Eng. 25(14–15), 2258–2271 (2005)CrossRef
12.
Schalbart, P., Haberschill, P.: Simulation of the behaviour of a centrifugal chiller during quick start-up. Int. J. Refrig. 36(1), 222–236 (2013)CrossRef
13.
Grald, E.W., MacArthur, J.W.A.: Moving-boundary formulation for modeling time-dependent two-phase flows. Int. J. Heat Fluid Flow 13(3), 266–272 (1992)CrossRef
14.
Willatzen, M., Pettit, N.B.O.L., Ploug-Sørensen, L.: A general dynamic simulation model for evaporators and condensers in refrigeration. Part I: moving-boundary formulation of two-phase flows with heat exchange. Int. J. Refrig. 21(5), 398–403 (1998)CrossRef
15.
Nyers, J., Stoyan, G.: A dynamical model adequate for controlling the evaporator of a heat pump. Int. J. Refrig. 17(2), 101–108 (1994)CrossRef
16.
He, X., Liu, S., Asada, H.H.: Modeling of vapor compression cycles for multivariable feedback control of HVAC systems. ASME J. Dyn. Syst. Measur. Control 119(2), 183–191 (1997)MATHCrossRef
17.
McKinley, T.L., Alleyne, A.G.: An advanced nonlinear switched heat exchanger model for vapor compression cycles using the moving-boundary method. Int. J. Refrig. 31(7), 1253–1264 (2008)CrossRef
18.
Cecchinato, L., Mancini, F.: An intrinsically mass conservative switched evaporator model adopting the moving-boundary method. Int. J. Refrig. 35(2), 349–364 (2012)CrossRef
19.
Bell, I.H., Quoilin, S., Georges, E., Braun, J.E., Groll, E.A., Horton, W.T., Lemort, V.: A generalized moving-boundary algorithm to predict the heat transfer rate of counterflow heat exchangers for any phase configuration. Appl. Therm. Eng. 79(3), 192–201 (2015)CrossRef
20.
Bendapudi, S., Braun, J.E., Groll, E.A.: A comparison of moving-boundary and finite-volume formulations for transients in centrifugal chillers. Int. J. Refrig. 31(8), 1437–1452 (2008)CrossRef
21.
Jin, G.Y., Cai, W.J., Lu, L., Lee, E.L., Chiang, A.: A simplified modeling of mechanical cooling tower for control and optimization of HVAC systems. Energy Convers. Manag. 48(2), 355–365 (2007)CrossRef
22.
Kloppers, C., Kroger, G.: Cooling tower performance evaluation: Merkel, Poppe, and e-NTU methods of analysis. J. Eng. Gas Turbines Power 127(1), 1–7 (2005)CrossRef
23.
Tan, K., Deng, S.: A numerical analysis of heat and mass transfer inside a reversibly used water cooling tower. Build. Environ. 38(1), 91–97 (2003)CrossRef
24.
Fisenko, S.P., Petruchik, A.I., Solodukhin, A.D.: Evaporative cooling of water in a natural draft cooling tower. Int. J. Heat Mass Transf. 45(23), 4683–4694 (2002)MATHCrossRef
25.
Fisenko, S.P., Brin, A.A., Petruchik, A.I.: Evaporative cooling of water in a mechanical draft cooling tower. Int. J. Heat Mass Transf. 47(1), 165–177 (2004)MATHCrossRef
26.
Mirth, D.R., Ramadhyani, S., Hittle, D.C.: Thermal performance of chilled-water cooling coils operating at low water velocities. ASHRAE Trans. 99(1), 43–53 (1993)
27.
Yu, X., Wen, J., Smith, T.F.: A model for the dynamic response of a cooling coil. Energy Build. 37(12), 1278–1289 (2005)CrossRef
28.
Threlkeld, J.L.: Thermal Environmental Engineering, 2nd edn. Prentice-Hall, Engledood Cliffs (1970)
29.
Mullen, C.E., Bridges, B.D., Porter, K.J., Hahn, G.W., Bullard, C.W.: Development and validation of a room air-conditioning simulation model. ASHRAE Trans. 104(1), 389–397 (1998)
30.
Deng, S.M.: A dynamic mathematical model of a direct expansion (DX) water cooled air-conditioning plant. Build. Environ. 35(7), 603–613 (2000)CrossRef
31.
Wang, J., Hihara, E.: Prediction of air coil performance under partially wet and totally wet cooling conditions using equivalent dry-bulb temperature method. Int. J. Refrig. 26(3), 293–301 (2003)CrossRef
32.
Bielski, S., Malinowski, L.: An analytical method for determining transient temperature field in a parallel-flow three-fluid heat exchanger. Int. Commun. Heat Mass Transfer 32(8), 1034–1044 (2005)CrossRef
33.
Yin, J.: M. Jensen K. Analytic model for transient heat exchanger response. Int. J. Heat Mass Transf. 46(17), 3255–3264 (2003)MATHCrossRef
34.
Ren, C., Yang, H.: An analytical model for the heat and mass transfer processes in indirect evaporative cooling with parallel/counter flow configurations. Int. J. Heat Mass Transf. 49(3–4), 617–627 (2006)MATH
35.
Xia, L., Chan, M.Y., Deng, S.M., Xu, X.G.: Analytical solutions for evaluating the thermal performances of wet air cooling coils under both unit and non-unit Lewis factors. Energy Convers. Manag. 51(10), 2079–2086 (2010)CrossRef
36.
Yao, Y., Lian, Z., Hou, Z.: Thermal analysis of cooling coils based on a dynamic model. Appl. Therm. Eng. 24(7), 1037–1050 (2004)CrossRef
37.
Yao, Y., Huang, M., Mo, J., Dai, S.: State-space model for transient behavior of water-to-air surface heat exchanger. Int. J. Heat Mass Transfer 66(9), 173–192 (2013)CrossRef
38.
Eppelheimer, D.M.: Variable flow—the quest for system energy efficiency. ASHRAE Trans. 102(2), 673–678 (1996)
39.
Carrdo, V., Mazza, A.: Axial fan. IEA annex 17 Report, Politecnico Ditorino, Italy (1991)
40.
Wang, S.W.: Dynamic simulation of a building central chilling system and evaluation of EMCS on-line control strategies. Build. Environ. 33(1), 1–20 (1998)CrossRef
41.
Shao, L., Riffat, S.B.: Accuracy of CFD for predicting pressure losses in HVAC duct fittings. Appl. Energy 51(3), 233–248 (1995)CrossRef
42.
Fisk, W.J., Delp, W., Diamond, R.: Duct systems in large commercial buildings: physical characterization, air leakage, and heat conduction gains. Energy Build. 32(1), 109–119 (2000)CrossRef
43.
Rokni, M., Gatski, T.B.: Predicting turbulent convective heat transfer in fully developed duct flows. Int. J. Heat Fluid Flow 22(4), 381–392 (2001)CrossRef
44.
Sugiyama, H., Akiyama, M., Nemoto, Y., Gessner, F.B.: Calculation of turbulent heat flux distributions in a square duct with one roughened wall by means of algebraic heat flux models. Int. J. Heat Fluid Flow 23(1), 13–21 (2002)CrossRef
45.
Wu, S., Sun, J.Q.: A physics-based linear parametric model of room temperature in office buildings. Build. Environ. 50(1), 1–9 (2012)CrossRef
46.
Abdul, A., Farrokh, J.S.: Review of modeling methods for HVAC systems. Appl. Therm. Eng. 67(1–2), 507–519 (2014)
47.
Metha, D.P., Woods, J.E.: An experimental validation of a rational model of dynamic responses of building. ASHRAE Trans. 86(1), 546–558 (1980)
48.
Borresen, B.A.: Thermal room models for control analysis. ASHRAE Trans. 87(2), 251–260 (1981)
49.
Tashtoush, B., Molhim, M., Al-Rousan, M.: Dynamic model of an HVAC system for control analysis. Energy 30(10), 1729–1745 (2005)CrossRef
50.
Riederer, P., Marchio, D., Visier, J.C., Husaunndee, A., Lahrech, R.: Room thermal modeling adapted to the test of HVAC control systems. Build. Environ. 37(8–9), 777–790 (2002)CrossRef
51.
Chen, Q., Peng, X., Paassen, A.H.C.V.: Prediction of room thermal response by CFD technique with conjugate heat transfer and radiation models. ASHRAE Trans. 101(part 1), 50–60 (1995)
52.
Wu, X., Olesen, B., Fang, W., Zhao, L.: A nodal model to predict vertical temperature distribution in a room with floor heating and displacement ventilation. Build. Environ. 59(1), 626–634 (2013)CrossRef
53.
Yao, Y., Yang, K., Huang, M.: A state-space model for dynamic response of indoor air temperature and relative humidity. Build. Environ. 64(6), 26–37 (2013)CrossRef
54.
Huang, G., Wang, S., Xu, X.: Robust model predictive control of VAV air-handling units concerning uncertainties and constraints. HVAC R. Res. 16(1), 15–33 (2010)MathSciNetCrossRef
55.
Huang, G.: Model predictive control of VAV zone thermal systems concerning bi-linearity and gain nonlinearity. Control Eng. Pract. 19(7), 700–710 (2011)CrossRef
56.
Wang, S., Zhou, Q., Xiao, F.: A system-level fault detection and diagnosis strategy for HVAC systems involving sensor faults. Energy Build. 42(4), 477–490 (2010)CrossRef
57.
Hosoz, M., Ertunc, H.M.: Artificial neural network analysis of an automobile air conditioning system. Energy Convers. Manag. 47(11–12), 1574–1587 (2006)CrossRef
58.
Ertunc, H.M., Hosoz, M.: Comparative analysis of an evaporative condenser using artificial neural network and adaptive neuro-fuzzy inference system. Int. J. Refrig. 31(8), 1426–1436 (2008)CrossRef
59.
Ding, L., Lv, J., Li, X., Li, L.: Support vector regression and ant colony optimization for HVAC cooling load prediction. In: International Symposium on Computer Communication Control and Automation (3CA), vol. 1 IEEE, Tainan, Taiwan, pp. 537–541 (2010)
60.
Becker, M., Oestreich, D., Hasse, H., Litz, L.: Fuzzy control for temperature and humidity in refrigeration systems. IEEE Trans., FM-4-2: 1607–1611 (1994)
61.
He, M., Cai, W.J., Li, S.Y.: Multiple fuzzy model-based temperature predictive control for HVAC systems. Inf. Sci. 169(1), 155–174 (2005)MATHCrossRef
62.
Soyguder, S., Alli, H.: An expert system for the humidity and temperature control in HVAC systems using ANFIS and optimization with fuzzy modeling approach. Energy Build. 41(3), 814–822 (2009)CrossRef
63.
Homoda, R.Z., Saharia, K.S.M., Almuribb, H.A.F., Nagia, F.H.: Gradient auto-tuned Takagi-Sugeno fuzzy forward control of a HVAC system using predicted mean vote index. Energy Build. 49(6), 254–267 (2012)CrossRef
64.
Khan, M.W., Choudhry, M.A., Zeeshan, M., Ali, A.: Adaptive fuzzy multivariable controller design based on genetic algorithm for an air handling unit. Energy 81(3), 477–488 (2015)CrossRef
65.
Mustafaraj, G., Chen, J., Lowry, G.: Development of room temperature and relative humidity linear parametric models for an open office using BMS data. Energy Build. 42(3), 348–356 (2010)CrossRef
66.
Penya, Y.K., Borges, C.E., Agote, D., Fernandez, I.: Short-term load forecasting in air-conditioned non-residential Buildings. In: 20th IEEE International Symposium on Industrial Electronics (ISIE), Gdansk, Poland, 1359–1364 27–30 June 2011
67.
Wang, Y.W., Cai, W.J., Soh, Y.C., Li, S.J., Lu, L., Xie, L.: A simplified modeling of cooling coils for control and optimization of HVAC systems. Energy Convers. Manag. 45(18–19), 2915–2930 (2004)CrossRef
68.
Ghiaus, C., Chicinas, A., Inard, C.: Grey-box identification of air-handling unit elements. Control Eng. Pract. 15(4), 421–433 (2007)CrossRef
69.
Yao, Y., Liu, S.: Transfer function model for dynamic response of wet cooling coils. Energy Convers. Manag. 49(12), 3612–3621 (2008)CrossRef
70.
Ferkl, L., Siroky, J.: Ceiling radiant cooling: comparison of ARMAX and sub-space identification modelling methods. Build. Environ. 45(2), 205–212 (2010)CrossRef
71.
Jiang, Y.: State space method for analysis of the thermal behavior of rooms and calculation of air-conditioning load. ASHRAE Trans. 101(1), 122–132 (1995)
72.
He, X.D., Liu, S., Asada, H.H., Itoh, H.: Multivariable control of vapor compression systems. HVAC&R Res. 4(3), 205–230 (1998)CrossRef
73.
Yao, Y., Huang, M., Yang, K.: State-space model for dynamic behavior of vapor compression liquid chiller. Int. J. Refrig. 36(8), 2128–2147 (2013)CrossRef
74.
Li, M., Wu, C.L., Zhao, S.Q., Yang, Y.: State-space model for airborne particles in multizone indoor environments. Atmos. Environ. 42(21), 5340–5349 (2008)CrossRef
75.
Qi, Q., Deng, S.: Multivariable control-oriented modeling of a direct expansion (DX) air conditioning (A/C) system. Int. J. Refrig. 31(5), 841–849 (2008)CrossRef
76.
Kumar, M., Kar, I.N., Ray, A.: State space based modeling and performance evaluation of an air-conditioning system. HVAC R Res. 14(5), 797–816 (2008)CrossRef
77.
Moroşan, P.D., Bourdais, R., Dumur, D., Buisson, J.: Building temperature regulation using a distributed model predictive control. Energy Build. 42(9), 1445–1452 (2010)CrossRef
78.
Prívara, S., Široký, J., Cigler, J.: Model predictive control of a building heating system: the first experience. Energy Build. 43(2–3), 564–572 (2011)CrossRef
79.
Balakrishnan, V.K.: Graph Theory. Shaum’s Outline Series, New York (1997)MATH
80.
Garg, R.K., Agrawal, V.P., Gupta, V.K.: Selection of power plants by evaluation and comparison using graph theoretic methodology. Electr. Power Energy Syst. 28(3), 429–435 (2006)CrossRef
81.
Prabhakaran, R.T.D., Agrawal, V.P.: Structural modeling and analysis of composite product system: a graph theoretic approach. J. Compos. Mater. 40(22), 1987–2007 (2006)CrossRef
82.
Grekas, D.N., Frangopoulos, C.A.: Automatic synthesis of mathematical models using graph theory for optimisation of thermal energy systems. Energy Convers. Manag. 48(12), 2818–2826 (2007)CrossRef
83.
Singh, V., Agrawal, V.P.: Structural modelling and integrative analysis of manufacturing systems using graph theoretic approach. J. Manuf. Technol. Manage. 19(7), 844–870 (2008)CrossRef
84.
Wang, T., Ding, G., Duan, Z., Ren, T., Chen, J., Pu, H.: A distributed-parameter model for LNG spiral wound heat exchanger based on graph theory. Appl. Therm. Eng. 81(1), 102–113 (2015)CrossRef
85.
Braun, J.E.: Reducing energy costs and peak electrical demands through optimal control of building thermal storage. ASHRAE Trans. 96(part 1), 587–601 (1990)
86.
Kawashima, M., Dorgan, C.E., Mitchell, J.W.: Hourly thermal load prediction for the next 24 hours by ARIMA, EWMA, LR, and an artificial neural network. ASHRAE Trans. 101(part 1), 186–200 (1995)
87.
Hwang, R.C., Huang, H.C., Chen, Y.J., Hsieh, J.G., Chen, H.C., Chuang, C.W.: Selection of influencing factors for power load forecasting by grey relation analysis. In: Second National Conference on Grey Theory and Applications, Taiwan, pp. 109–113 (1997)
88.
Neto, A.H., Fiorelli, F.A.S.: Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption. Energy Build. 40(12), 2169–2176 (2008)CrossRef
89.
Zhou, Q., Wang, S., Xu, X., Xiao, F.: A grey-box model of next-day building thermal load prediction for energy-efficient control. Int. J. Energy Res. 32(15), 1418–1431 (2008)CrossRef
90.
Guo, J.J., Wu, J.Y., Wang, R.Z.: A new approach to energy consumption prediction of domestic heat pump water heater based on grey system theory. Energy Build. 43(6), 1273–1279 (2011)CrossRef
91.
Chen, H.: The Validity of the Theory and Its Application of Combination Forecast Methods. Science Press, Beijing (China) (2008)
92.
Granger, C.W.J., Ramanathan, R.: Improved methods of combining forecasts. J. Forecast. 3(3), 197–204 (1984)CrossRef
93.
Braun, J.E., Klein, S.A., Mitchell, J.W., Beckman, W.A.: Methodologies for optimal control of chilled water systems without storage. ASHRAE Transact. 95(1), 652–662 (1989)
94.
Olson, R.T., Liebman, S.: Optimization of a chilled water plant using sequential quadratic programming. Eng. Optim. 15(1), 171–191 (1990)CrossRef
95.
Ahn, B.C., Mitchell, J.W.: Optimal control development for chilled water plants using a quadratic representation. Energy Build. 33(4), 371–378 (2001)CrossRef
96.
Chang, Y.C.: Application of genetic algorithm to the optimal chilled water supply temperature calculation of air-conditioning systems for saving energy. Energy Res. 31(8), 796–810 (2007)CrossRef
97.
Engdahl, F., Johansson, D.: Optimal supply air temperature with respect to energy use in a variable air volume system. Energy Build. 36(3), 205–218 (2004)CrossRef
98.
Xu, X., Wang, S., Sun, Z., Xiao, F.: A model-based optimal ventilation control strategy of multi-zone VAV air-conditioning systems. Appl. Therm. Eng. 29(1), 91–104 (2009)CrossRef
99.
Mossolly, M., Ghali, K., Ghaddar, N.: Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm. Energy 34(1), 58–66 (2009)CrossRef
100.
Sun, J., Reddy, A.: Optimal control of building HVAC and R systems using complete simulation-based sequential quadratic programming (CSB-SQP). Build. Environ. 40(5), 657–669 (2005)CrossRef
101.
Hanby, V.I., Wright, J.A.: HVAC optimization studies: component modeling methodology. Build. Serv. Eng. Res. Technol. 10(1), 35–39 (1989)CrossRef
102.
Zaheer-Uddin, M., Zheng, G.R.: Optimal control of time-scheduled heating, ventilating and air conditioning processes in buildings. Energy Convers. Manag. 41(1), 49–60 (2000)CrossRef
103.
Chow, T.T., Zhang, G.Q., Lin, Z., Song, C.L.: Global optimization of absorption chiller system by generic algorithm and neural network. Energy Build. 34(1), 103–109 (2000)CrossRef
104.
Huang, L.: Using genetic algorithms to optimize controller parameters for HVAC systems. Energy Build. 26(2), 277–282 (1997)CrossRef
105.
Fong, K.F., Hanby, V.I., Chow, T.T.: System optimization for HVAC energy management using the robust evolutionary algorithm. Appl. Therm. Eng. 29(11–12), 2327–2334 (2009)CrossRef
106.
Kido, T., Takag, K., Nakanishi, M.: Analysis and comparisons of genetic algorithm, simulated annealing, TABU search, and combination algorithm. Informatics 18(4), 399–410 (1994)
107.
Arturo, M.C., Lorenz, T.B.: A stable elemental decomposition for dynamic process optimization. J. Comput. Appl. Math. 120(1), 41–57 (2000)MathSciNetMATH
108.
Thi, H.A.L., Pham, D.T., Thoai, N.V.: Combination between global and local methods for solving an optimization problem over the efficient set. Eur. J. Oper. Res. 142(2), 258–270 (2002)MathSciNetMATHCrossRef
109.
Huang, Y.J., Reklaitis, G.V., Venkatasubramanian, V.: Model decomposition based method for solving general dynamic optimization problems. Comput. Chem. Eng. 26(6), 863–873 (2002)CrossRef
110.
111.
Yu, D., Li, H., Ni, L., Yu, Y.: An improved virtual calibration of a supply air temperature sensor in rooftop air conditioning units. HVAC & R Res. J. 17(5), 798–812 (2011)
112.
United Nations.: Role of measurement and calibration in the manufacture of products for the global market (2006)
113.
Li, Z., Huang, G.: Preventive approach to determine sensor importance and maintenance requirements. Autom. Constr. 31(3), 307–312 (2013)
114.
Huang, Y., Qian, X., Chen, S.: Multi-sensor calibration through iterative registration and fusion. Comput. Aided Des. 41(2), 240–255 (2009)CrossRef
115.
Djuric, N., Huang, G., Novakovic, V.: Data fusion heat pump performance estimation. Energy Build. 43(6), 621–630 (2011)CrossRef
116.
Mitchell, H.B.: Data Fusion: Concepts and Ideas, 2nd ed. Springer (2012)
117.
Yu, D., Li, H., Yu, Y., Xiong, J.: Virtual calibration of a supply air temperature sensor in rooftop air conditioning units. HVAC&R Res. 17(1), 31–50 (2011)CrossRef
118.
Whitehouse, K., Culler, D.: Calibration as parameter estimation in sensor networks. In: Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications, pp. 59–67 (2002)
119.
Bychkovskiy, V., Megerian, S., Estrin, D., Potkonjak, M.: A collaborative approach to in-place sensor calibration. Lect. Notes Comput. Sci. 263(2), 301–316 (2003)MATHCrossRef
120.
Dulev, V., Ermishin, S., Khoteev, N., Lopatin, A., Shabanov, P., Menshikov, A., Startsev, A.: Automated measuring system designed to calibrate measuring devices using virtual standards technology. In: 2004 IEEE Autotestcon, pp. 158–164
121.
Fisher, J.W., Moses, R.L., Willsky, A.S.: Nonparametric Belief Propagation for Self-calibration in Sensor Networks. IPSN’ 04, Berkeley, California, 26–27 April 2004
122.
Balzano, L., Nowak, R.: Blind calibration of sensor networks. In: Proceedings of IPSN’07. Cambridge, Massachusetts, 25–27 April 2007
123.
Yu, D., Li, H., Yang, M.: A virtual supply airflow rate meter for rooftop air-conditioning units. Build. Environ. 46(6), 1292–1302 (2011)CrossRef
124.
Tan, R., Xing, G., Liu, X., Yao, J., Yuan, Z.: Adaptive calibration for fusion-based cyber-physical system. ACM Trans. Embed. Comput. Syst. 11(4), 80, (1–25) (2012)
125.
Mosh, B., Rashidi, F.: Self-tuning based fuzzy PID controllers: application to control of nonlinear HVAC systems. In: Proceedings of 5th International conference: Intelligent Data Engineering and Automated Learning. Exeter, UK (2004)
126.
Yu, Y.: Model-based multivariate control of conditioning systems for office buildings (PhD. thesis). Carnegie Mellon University (2012)
127.
Rawlings, J.B., Mayne, D.Q.: Model Predictive Control: Theory and Design. Nob Hill Publishing (2009)
128.
Camacho, E.F., Bordons, C.: Model Predictive Control in the Process Industry. Springer, Berlin (1995)
129.
Qin, S.J., Badgwell, T.A.: A survey of industrial model predictive control technology. Control Eng. Pract. 11(7), 733–764 (2003)CrossRef
130.
Zhang, Y., Hanby, V.I.: Model-based control of renewable energy systems in buildings. HVAC&R Res. 12(3a), 739–760 (2006)CrossRef
131.
Yuan, S., Perez, R.: Multiple-zone ventilation and temperature control of a single-duct VAV system using model predictive strategy. Energy Build. 38(10), 1248–1261 (2006)CrossRef
132.
Wang, S., Ma, Z.: Supervisory and optimal control of building HVAC systems: a review. HVAC&R Res. 14(1), 3–32 (2008)CrossRef
133.
Freire, R.Z., Oliveira, G.H.C., Mendes, N.: Predictive controllers for thermal comfort optimization and energy savings. Energy Build. 40(7), 1352–1365 (2008)CrossRef
134.
Hazyuk, I., Ghiaus, C., Penhouet, D.: Optimal temperature control of intermittently heated buildings using model predictive control: part II—control algorithm. Build. Environ. 51(5), 388–394 (2012)CrossRef
Metadata
Title
Introduction
Authors
Ye Yao
Yuebin Yu
Copyright Year
2017
Publisher
Springer Berlin Heidelberg
Book
Modeling and Control in Air-conditioning Systems

Print ISBN: 978-3-662-53311-6

Electronic ISBN: 978-3-662-53313-0

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-662-53313-0_1