Short Review on Controller Design Approaches of Heating Ventilation Air Conditioner Systems Towards Energy-Efficient Buildings
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)
The paper gives an overview of heating, ventilation and air-conditioning (HVAC) system and controller design approaches towards energy-efficient. The controller design approaches for the HVAC system can be categorized into the 3 main classes, which are the classical control approach, modern control approach and artificial intelligence control approach. Each category consists of different type of controllers which are presented. In classical controller approaches ‘ON’ and ‘OFF’ or PID controllers are the most significant influence to control the HVAC system whereas the modern control approach is used to reduce the weakness of the classical control approach. The artificial control approach is used to multi-criteria objectives of thermal comfort and energy saving without any need to mathematically model the system. The characteristics, as well as the advantage and limitation for each strategy are presented
Copyright © 2014 Praise Worthy Prize - All rights reserved.
L. J. Wei, The system identification of HVAC using artificial neural network, MSc dissertation, Dept. Mech. Eng., Technology Malaysia Univ., JB, 2012.
C. Benton, HVAC components and systems, Energy Foundation and the PG&E Energy Center1993.
CIBSE Guide, energy efficiency in buildings (CIBSE Guide F) (Chartered Institution of Building Services Engineers 2006).
R. A. Shoureshi, Intelligent control systems: are they for real?, Transactions of the ASME, Journal of Dynamic Systems, Measurement, and Control, vol. 115 n. 2B, Febuary 1993, pp. 392-401.
T. Matsuba, M. Kasahara, I. Murasawa, Stability Limit of Room Air Temperature of a VAV System, ASHRAE Transactions, vol. 104 n. 2, 1999, pp. 257-265.
G. M. Maxwell, H. N. Shapiro, D. G. Westra, Dynamics and control of a chilled water coil, ASHRAE Transactions, vol. 95 n. 1, 1989, pp. 1243–1255.
G. Geng, G. M. Geary, On performance and tuning of PID controllers in HVAC systems, Proc. IEEE Conf. Contr. Applicat., Sepember, 13-16, 1993, Vancouver, BC.
J. E. Seem, A new pattern recognition adaptive controller with application to HVAC systems, Automatica, vol. 34 n. 8, August 1998, pp. 969-982.
K. I. Krakow, S. Lin, PI control of fan speed to maintain constant discharge pressure, ASHRAE Transactions, vol. 101 n. 2, 1995, pp. 398-407.
M. J. Pinnella, E. Wechselberger, D. C. Hittle, C. O. Pederson, Self-tuning digital integral control, ASHRAE Transactions, vol. 92 n. 2B, 1986, pp. 202-210.
C. G. Nesler, W. F. Stoecker, Selecting the Proportional and Integral Constants in the Direct Digital Control of Discharge Air Temperature, ASHRAE Transactions, vol. 90 n. 2B, 1984, pp. 834–845.
G. Shaavit, S. G. Brandt, the dynamic performance of a discharge air temperature system with a P-I controller (Honeywell Inc., commercial division, 1982).
K. Masato, M. Tadahiko, H. Yukihiro, M. Itaru, K. Akiomi, K. Kazuyuki, K. Shigeru, Optimal preview control for HVAC system, ASHRAE Transactions, vol. 104 n. 1, 1998, pp. 502–513.
G. R. Zheng, M. Zaheer-Uddin, Discharge air system: Modelling and optimal control, International Journal of Energy Research, vol. 23 n. 8, Jun 1999, pp. 727–738.
J. M. House, S. Theodrof, Optimal control of building and HVAC systems, Proceeding American Control Conference, Jun, 21-23, 1995, Seattle, WA.
S. Biao, B. Peter, F. Luh, An Integrated Control of Shading Blinds, Natural Ventilation, and HVAC Systems for Energy Saving and Human Comfort, 6th annual IEEE Conference on Automation Science and Engineering, August, 21-24, 2010, Toronto, ON.
G. Moeseke, I. Bruyere, A. D. Herde, Impact of control rules on the efficiency of shading devices and free cooling for office buildings, Building and Environment, vol. 42 n. 2, Febuary 2007, pp. 784-793.
M. Mossolly, K. Ghali, N. Ghaddar, Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm Energy, vol. 34 n. 1, January 2009, pp. 58-66.
A. Tzempelikos, A. K. Athienitis, Investigation of Lighting, Daylighting and Shading Design Options for New Concordia University Engineering Building, Proceedings of eSim2002 Building Simulation Conference, Montreal, Canada, 2002, Montreal, Canada.
J. Xu, P. B. Luh, W. E. Blankson, R. Jerdonek, K. Shaikh, An optimization-based approach for facility energy management with uncertainties, HVAC&R Research, vol. 11 n. 2, April 2005, pp. 215-237.
M. Zaheer-uddin, Optimal control of a single zone environmental space, Building and Environment, vol. 27 n. 1, January 1992, pp. 93–103.
M. Zaheer-uddin, R. V. Patel, THE DESIGN AND SIMULATION OF A SUB-OPTIMAL CONTROLLER FOR SPACE HEATING, ASHRAE Trans., 1993.
M. Zaheer-Uddin, R. V. Patel, S. A. K. Al-Assadi, Design of decentralized robust controllers for multizone space heating systems, IEEE Trans. Contr. Syst. Technol, 1993.
M. Zaheer-uddin, R. V. Patel, S. A. K. Al-assadi, Decentralized control of a variable air volume system, American Control Conference, June 29, July 1, 1994.
T. Tigrek, S. Dasgupta, T. F. Smith, Nonlinear optimal control of HVAC systems, presented at the 15th IFACWorld Congr., 2002, Barcelona.
C. Rentel-Gomez, M. Velez-Reyes, Decoupled control of temperature and relative humidity using variable-air-volume HVAC system and non-interacting control, In Proc. IEEE int. conf. contr. applicat., September, 5-7, 2001, Mexico City.
M. Zaheeruddin, R. Patel, Optimal tracking control of multi-zone indoor environmental spaces, ASME J Dyn Syst, Measurement & Control, vol. 117 n. 3, September 1995, pp. 292-303.
E. Semsar, M. J. Yazdanpanah, C. Lucas, Nonlinear control anddisturbance decoupling of an HVAC system via feedback linearization and back-stepping, Proc. IEEE int. conf on control applications, 2003.
K. J. Astrom, T. Hagglund, PID controllers: theory, design, and tuning (Instrument Society of America, research triangle park, 1995).
American Society of Heating, 2003 ASHRAE handbook : heating, ventilating, and air-conditioning applications : inch-pound edition (Amer Society of Heating 2003).
A. Beghi, L. Cecchinato, Modelling and Adaptive Control of Small Capacity Chillers for HVAC Applications, Applied Thermal Engineering, vol. 31 n. 6–7, May 2011, pp. 1125-1134.
S. S. Sastry, A. Isidori, Adaptive control of linearizable systems, Automatic Control, IEEE Transactions on, vol. 34 n. 11, November 1989, pp. 1123-1131.
D. Garagiic, K. Srinivasan, Application of Nonlinear Adaptive Control Techniques to an Electrohydraulic Velocity Servomechanism, IEEE transaction on control system technology, vol. 12 n. 2, March 2004, pp. 303-314.
X. Ma, G. Tao, Adaptive actuator compensation control with feedback linearization, Automatic Control, IEEE Transactions on, vol. 45 n. 9, September 2000, pp. 1705-1710.
Z. Huaguang, L. Cai, Decentralized nonlinear adaptive control of an HVAC system, IEEE Trans. System, Man, and Cybernetics, Part C: Applications and Reviews, vol. 32 n. 4, February 2003, pp. 493-498.
H. Zhang, C. Lilong, Decentralized nonlinear adaptive control of an HVAC system, Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 32 n. 4, November 2002, pp. 493-498.
F. Garelli, R. J. Mantz, H. De Battista, Limiting Interactions in Decentralized Control of MIMO Systems, Process Control, vol. 16 n. 5, June 2006, pp. 473- 483.
B. Qiang, C. Wen-Jian, W. Qing-Guo, H. Chang-Chieh, L. Eng-Lock, S. Yong, D. L. Ke, Z. Yong, Z. Biao, Advanced controller auto-tuning and its application in HVAC systems, Control Engineering Practice, vol. 8 n. 6, June 1999, pp. 633-644.
W. Jiangjiang, J. Youyin, A. Dawei, Study of Neuron Adaptive PID Controller in a Single-zone HVAC System, Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on, 30 Augest, 1 Sepember, 2006, Beijing.
Y. H. Chen, K. M. Lee, W. J. Wepfer, Adaptive robust control scheme applied to a single-zone HVAC system, In Proc. Amer. Control Conf., May, 23-35, 1990, San Diego, CA, USA.
C. P. Underwood, Robust control of HVAC plant II: Controller design, Building Services Engineering Research and Technology, vol. 21 n. 1, January 2000, pp. 63–71.
M. Kasahara, T. Matsuba, Y. Kuzuu, T. Yamazaki, Y. Hashimoto, K. Kamimura, S. Kurosu, Design and Tuning of Robust PID Controllerfor HVAC Systems, ASHRAE Trans., vol. 105 n. 2, June 1999, pp. 154–166.
X. He, S. Liu, H. H. Asada, H. Itoh, Multivariable control of vapor compression systems, International Journal HVAC&R Research, vol. 4 n. 3, Febuary 2011, pp. 205–230.
S. W. Wang, X. H. Xu, Optimal and robust control of outdoor ventilation airflow rate for improving energy efficiency and IAQ, Building Environment, vol. 39 n. 7, July 2004, pp. 763–773.
L. Xuquan, S. Zhigang, H. Songtao, A novel control method of a variable volume air conditiong system for indoor thermal environment, Computer Engineering and Technology (ICCET), 2010 2nd International Conference on, April, 16-18, 2010, Chengdu.
M.-L. Chiang, L.-C. Fu, Adaptive and robust control for nonlinear HVAC system, International conference on systems, man, and cybernetics, October, 8-11, 2006, Taipei.
M. L. Anderson, P. M. Young, D. C. Hittle, C. W. Anderson, J. T. Hodgson, D. Hodgson, MIMO robust control for heating, ventilating and air conditioning (HVAC) systems, In Proc. IEEE Conf. Decision Contr., December 10-13, 2002.
D. M. Underwood, R. R. Crawford, Dynamic nonlinear modeling of a hot-water-to-air heat exchanger for control applications, ASHRAE Trans., vol. 96 n., 1990, pp. 149–155.
Y. Zhang, E. M. Brber, H. C. Wood, ANALYSIS OF STABILITY OF LIVESTOCK BUILDING HEATING/VENTILATION CONTROL SYSTEMS, ASHRAE Transactions, vol. 99 n. 2, 1993, pp. 237–244.
C. P. Underwood, Robust control of HVAC plant II: Controller design,, CIBSE J., vol. 21, no. 1 n., 2000, pp. 63–72.
M. J. Yazdanpanah, E. Semsar, C. Lucas, Minimization of actuator repositioning in delayed processes using flexible neural networks, Control Applications, 2003. CCA 2003. Proceedings of 2003 IEEE Conference on, June, 23-25, 2003.
M. R. Omidi, M. J. Yazdanpanah, Minimization of actuator repositioning using internal model control, 4th Portuguese Conference on Automatic Control, January, 1, 2000.
H. Mirinejad, K. C. Welch, L. Spicer, A review of intelligent control techniques in HVAC systems, Energy tech., 2012, Cleveland, OH.
J. Yang, H. Rivard, R. Zmeureanu, On-line building energy prediction using adaptive artificial neural networks, Energy and Buildings, vol. 37 n. 12, December 2005, pp. 1250-1259.
M. J. Ismail, R. Ibrahim, I. Ismail, Adaptive neural network prediction model for energy consumption, Computer Research and Development (ICCRD), 2011 3rd International Conference on, March, 11-13, 2011, Shanghai.
E. Kaymaz, Adaptive environmental control for optimal energy consumption in hospitals, Proceedings of the 8th IEEE Symposium, 9-10 Jun, 1995, Lubbock, TX.
H. T. Nguyen, N. R. Prasad, C. L. Walker, E. A. Walker, first course in fuzzy and neural control (Chapman & Hall, 2003).
X. Qiang, C. Wen-Jian, H. Ming, A practical decentralized PID auto-tuning method for TITO systems under closed –loop control, International Journal of Innovative Computing, Information and Control, vol. 2 n. 2, April 2006, pp. 305-322.
W. Qiao, M. Masaharu, PID type fuzzy controller and parameters adaptive method, Fuzzy sets and systems, vol. 78 n. 1, Febuary1996, pp. 23-35.
W. Qing-Gao, H. Chang-Chieh, Z. Yong, B. Qiang, Multivariable Controller Auto-Tuning with its Application in HVAC Systems, proceeding of American Control Conference, Jun, 2-4, 1999, California.
R. K. Mudi, N. R. Pal, A robust self-tuning scheme for PI and PD type fuzzy controllers, Fuzzy Systems, IEEE Transactions on, vol. 7 n. 1, Febuary 1999, pp. 2-16.
M. H. Khooban, D. Nazari, M. Abadi, Optimal Type-2 Fuzzy controller for HVAC systems, 2011.
D. Kolokotsa, Comparison of the performance of fuzzy controllers for the management of the indoor environment, Building and Environment, vol. 38 n. 12, December 2003, pp. 1439-1450.
D. Kolokotsa, K. Niachou, V. Geros, K. Kalaitzakis, G. S. Stavrakais, M. Santamouris, Implementation of an integrated indoor environment and energy management system, Energy and Buildings, vol. 37 n. 1, January 2005, pp. 93-99.
A. K. Pal, R. K. Mudi, Self-Tuning Fuzzy PI Controller and its Application to HVAC Systems, INTERNATIONAL JOURNAL OF COMPUTATIONAL COGNITION, vol. 6 n. 1, March 2008, pp.
J. Liang, R. Du, Design of intelligent comfort control system with human learning and minimum power control strategies, Energy Conversion and Management, vol. 49 n. 4, April 2008, pp. 517-528.
R. Alcal´a, J. M. Ben´ttez, J. Casillas, O. Cordo´n, R. Pe´rez, Fuzzy Control of HVAC Systems Optimized by Genetic Algorithms, Applied Intelligence, vol. 18 n. 2, March 2003, pp. 155–177.
P. O. Fanger, thermal comfort, analysis and applications in environmental engineering (Mcgraw-hill, 1972).
M. J. Gacto, R. Alcala, F. Herrera, Evolutionary Multi-Objective Algorithm to Effectively Improve the Performance of the Classic Tuning of Fuzzy Logic Controllers for a Heating, Ventilating and Air Conditioning System, Applied Intelligence, vol. 36 n. 2, March 2012, pp. 330-347.
H. X. Li, L. Zhang, K. Y. Cai, G. Chen, An improved robust fuzzy-PID controller with optimal fuzzy reasoning, IEEE Trans. Sys., Man, and Cybern, vol. 35 n. 6, December 2005, pp. 1283-1294.
H. Ying, Practical design of nonlinear fuzzy controllers with stability analysis for regulating processes with unknown mathematical models, Automatica, vol. 30 n. 7, July 1994, pp. 1185–1195.
H. Mirinejad, S. H. Sadati, M. Ghasemian, H. Torab, Control techniques in heating, ventilating and air conditioning systems, Computer Science, vol. 4 n. 9, 2008, pp. 777-783.
M. Hamdi, G. Lachiver, A fuzzy control system based on the human sensation of thermal comfort, IEEE International Conferance on Fuzzy System, May, 4-9, 1998 Anchorage, AK.
F. Hoffmann, Evolutionary algorithms for fuzzy control system design, Proceeding of the IEEE, vol. 89 n. 9, September 2001, pp. 1318–1333.
O. Cordon, F. Herrera, F. Hoffmann, L. Magdalena, F. Gomide, Ten years of genetic fuzzy systems, Fuzzy sets abd systems, vol. 141 n. 1, January 2003, pp. 5-31.
S. Kajl, M. Roberge, L. Lamarche, P. Malinowski, Evaluation of building energy consumption based on fuzzy logic and neural networks applications, Belgium, Proceedings of Clima 2000 Conference, held Brussels, August 30, September 2, 1997, Belgium, Brussels.
A. Dhar, T. A. Reddy, D. E. Claridge, A Fourier Series Model to Predict Hourly Heating and Cooling Energy Use in Commercial Buildings with Outdoor Temperature as the Only Weather Variable, ASME Journal of Solar Energy Engineering, vol. 121 n. 1, Febueary 1999, pp. 47–53.
J. Yang, H. Rivard, R. Zmeureanu, On-line building energy prediction using adaptive artificial neural networks, Energy and Buildings, vol. 37 n. 12, 2005, pp. 1250-1259.
M. Anstett, J. F. Kreider, Application of Neural Networking Models to Predict Energy Use, ASHRAE Transactions, vol. 99 n. 1, 1993, pp. 505-517.
P. S. Curtiss, J. F. Kreider, M. J. Brandemuehl, Energy Management in Central HVAC Plants Using Neural Networks, ASHRAE Transactions, vol. 100 n. 1, 1994, pp. 476-493.
M. Fels, Special Issues Devoted to Measuring Energy Savings: the Scorekeeping Approach, Energy and Buildings, vol. 9 n. 2, 1986, pp. 5–18.
S. Katipamula, T. A. Reddy, D. E. Claridge, Multivariate regression modeling, ASME Journal of Solar Energy Engineering, vol. 120 n. 3, August 1998, pp. 177–184.
A. Kimbara, S. Kurosu, R. Endo, K. Kamimura, T. Matsuba, A. Yamada, On-line prediction for load profile of an air-conditioning system, ASHRAE Transactions, vol. 101 n. 2, 1995, pp. 198–207.
Y. Hong-Tzer, H. Chao-Ming, H. Ching-Lien, Identification of ARMAX model for short term load forecasting: an evolutionary programming approach, IEEE Transaction on Power Systems, May, 7-12, 1995, Salt Lake City, UT.
D. Datta, S. Tassou, Energy Management in Supermarkets Through Electrical load Prediction, 1st International Conferance on Energy and Environment, 1997, Limassol, cyprus.
J. Teeter, M. Y. Chow, Application of functional link neural network to HVAC thermal dynamic system identification, Industrial Electronics, IEEE Transactions on, vol. 45 n. 1, Febuary 1999, pp. 170–176.
K. J. Astrom, T. Hagglund, A. Wallenborg, Automatic Tuning of Digital Controllers with Applications to HVAC Plants, Automatica, vol. 29 n. 5, September 1993, pp. 1333–1343.
L. Shujiang, Z. Xiaoqing, X. Jinxue, C. Wenjian, An Improved Fuzzy RBF Based on Cluster and Its Application in HVAC System, Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on, 2006, Dalian.
P. Curtiss, M. Brandemuehl, J. Kreider, Energy management in central HVAC plants using neural networks., In: Haberl JS, Nelson RM, Culp CC, editors. The Use of Artificial Intelligence in Building Systems. ASHRAE, n., 1995, pp. 199–216.
F. Rashidi, Improving heat transfer efficiency in heating ventilation and air conditioning systems using a robust fuzzy PID controller, 2005.
W. Jian, C. Wenjian, Development of an adaptive neuro-fuzzy method for supply air pressure control in HVAC system, IEEE International Conf. on Systems, Man, and Cybernetics, n., 2000 pp.
W. Jian, C. Wenjian, Development of an adaptive neuro-fuzzymethod for supply air pressure control in HVAC system, IEEE International Conf. on Systems, Man, and Cybernetics, 2000, Nashville, TN.
Q. Bi, W. Cai, et al, Advanced Controller Auto-Tuning and Its Application in HVAC Systems, Control Engineering Practice, vol. 8 n. 6, June 2000, pp. 633-644.
K. P. Arabinda, Development of Neuro-Fuzzy Controller for Applications to HVAC System, Inverted Pendulum and Other Processes, Internal Journal Computational Cognition, vol. 6 n. 2, June 2008, pp. 1-6.
B. Moshiri, F. Rashidi, Self-tuning Based Fuzzy PID Controllers: Application to Control of Nonlinear HVAC Systems, In Z. Yang, H. Yin, and R. Everson,(ed.), Self-tuning Based Fuzzy PID Controllers: Application to Control of Nonlinear HVAC Systems, 64 (Springer Berlin Heidelberg, 2004, 437-442).
- There are currently no refbacks.
Please send any questions about this web site to firstname.lastname@example.org
Copyright © 2005-2018 Praise Worthy Prize