Development an Adaptive Incremental Fuzzy PI Controller for a HVAC System
AbstractThis paper presents an adaptive incremental fuzzy PI controller (AIFPI) for a heating, ventilating, and air conditioning (HVAC) system capable of maintaining comfortable conditions under varying thermal loads. The HVAC system has two subsystems and is used to control indoor temperature and humidity in a thermal zone. As the system has strong-coupling and non-linear characteristics, fixed PI controllers have poor control performance and more energy consumption. Aiming to solve the problem, fuzzy control and PI control are combined together organically. In the proposed control scheme, the error of the system output and its derivative are taken as two parameters necessary to adapt the proportional (P) and integral (I) gains of the PI controller based on fuzzy reasoning according to practical control experiences. To evaluate the effectiveness of the proposed control methods in the HVAC system, it is compared with a fixed well-tuned PI controller. The results demonstrate that the AIFPI controller has more superior performance than the latter.
 Salsbury, T., A survey of control technologies in the building automation industry, Proc. of the 16th IFAC World Congress, 331–341, 2005.
 Levine, W.S., Control System Applications, Boca Raton, CRC Press, 121-123, 2000.
 Astrom, K.J., Wittenmark, B., Adaptive control, Reading, Addison-Wesley, 1995.
 Bai, J., Zhang. X., A new adaptive PI controller and its application in HVAC systems, Energy Conversion and Management, 48(2): 1043-1054, 2007.
 Nesler, C.G., Automated Controller Tuning for HVAC Applications, ASHRAE Trans., 92(2B): 189-201, 1986.
 White, D.A., Sofge, D.A., Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches, Van Nostrand, Reinhold Comp., 1992.
 Ferreira, P.M., Ruano, A.E., Silva S., Neural networks based predictive control for thermal comfort and energy savings in public buildings, Energy and Buildings, 55(0): 238-251, 2012.
 Zaheer-uddin, M., Tudoroiu, N., Neuro-PID tracking control of a discharge airtemperature system, Energy Conversion and Management, 45(15-16): 2405-2415, 2004.
 Seem, J.E., Haugstad, H.J., Field and Laboratory Results for a New Pattern Recognition Adaptive Controller, Proc. of Clima 2000 Conference, 96-100, 2000.
 Chang, S.S.L., Zadeh, L.A., On fuzzy mapping and control. Systems, Man and Cybernetics, IEEE Trans. on, (1): 30-34, 1972.
 Arguello-Serrano, B., Velez-Reyes, M., Nonlinear control of a heating, ventilating, and air conditioning system with thermal load estimation, IEEE Transactions on Control Systems Technology, 7(1): 56-63, 1999.
 Wang, Q.G., Lee T.H., Fung, H.W. et al., PID tuning for improved performance, IEEE Trans. on Control Syst. Tech., 7(2): 457-465, 1999.
 Bi, Q., Cai W.J., Wang, Q.G. et al., Advanced controller auto-tuning and its application in HVAC systems, Control Eng. Practice, 8(6): 633-644, 2000.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.