Abstract
In order to eliminate the current negative condition of Automatic Computer Room Air-Conditioning (CRAC) system, self-tuning Fuzzy Logic Control (FLC) was designed and applied to fan speed in CRAC system. In this paper, we derive a thermodynamic model of a datacenter suitable for applying adaptive self-tuning PID-type fuzzy adaptive control theory. It combines the classic PID control strategy and fuzzy adaptive control theory. The classic PID control uses the error and rate of change of error as its inputs to control the temperature automatically, and the fuzzy logic controller is used in the self-tuning PID-type fuzzy control to tune the parameters of PID controller on-line by fuzzy control rules. Simulation and testing results show that the proposed self-tuning FLC method can achieve less steady-state error and short settling time in temperature control of datacenter.
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Bash, C.E., Patel, C.D., Sharma, R.K.: Efficient Thermal Management of Data Centers Immediate and Long-Term Research Needs. Intl. J. HVAC&R. Res. (2003)
Boucher, T.D., Auslander, D.M.: Viability of Dynamic Cooling Control in a Data Center Environment (2004)
Lee, E.K., Kulkarni, I., Pompili, D., Parashar, M.: Proactive Thermal Management in Green Datacenter. The Journal of Super-computing (2010)
Salsbury, T.I.: A temperature controller for VAV air-handing units based on simplified physical models. HVAC and R. Res. (1998)
Kasahara, M., Matsuba, T., Boucherand, T.D., Auslander, D.M.: Design and tuning of robust PID controller for HVAC system (1999)
Bi, Q., Cai, W.-J., Wang, Q.-G.: Advanced controller auto-tuning and its application in HVAC system (2000)
Shayeghi, H., Shayanfar, H.A., Jalili, A.: Multi stage fuzzy PID power system automatic generation controller in the deregulated environment. Energy Convers Manage (2006)
Shayeghi, H., Jalili, A., Shayanfar, H.A.: Robust modified GA based multi-stage fuzzy LFC. J Energy Convers Manage (2007)
Schmidt, R.R.: Thermal profile of a high-density data center-methodology to thermally characterize a data center. Trans Am Soc Heat RefrigAirCondEng, ASHRAE (2004)
Schmidt, R.R., Karki, K.C., Patankar, S.V.: Raised floor computer data center: perforated tile flow rates for various tile layouts Thermal profile of a high-density data center-methodology to thermally characterize a data center. In: Proc. of Intersociety Conference on Thermal Phenomena in Electronic Systems, ITHERM (2004)
Tao, Y.Y.H., New-style, G.Y.X.: PID control and application (2001)
Lei, L., Wang, H., Yu, Y.: Adaptive Fuzzy PID Control Method Based on Identification Structure. International Journal of System and Control (2006)
Yang, Y.: Application of MATLAB in PID Control Theory’s teaching Reform. Journal of Changshu Institute of Technology (2009)
Wang, S., Jiang, W.: PID Tuning Based on MATLAB/Simulink. Industry Control and Applications (2009)
Lu, R.: Matter-element Modeling of Parallel Structure and Application about Extension PID Control Syetem. Joural of Systems Science & Complexity (2006)
Wang, L., Du, W.: Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process. Journal of Natrual Gas Chemistry (2008)
Zi, B., Duan, B., Qiu, Y.: Fuzzy-PID control base on disturbance observer and its application.Systems Engineering and Electronics (2006)
Ma, Y., Liu, Y., Wang, C.: Design of Parameters Self-tuning Fuzzy PID Control for DC Motor. In: The 2nd International Conference on Industrial Mechatronics and Automation (ICIMA 2010) (2010)
Yu, Q.: Based on MATLAB’s Analysis of Steady-State Error in Control System. Journal of Changshu College (2004)
Liu, Y.: Study on boiler temperature system PID controlbased on RBF neural network. Journal of Baoji University of ArtsandSciences (Natural Science) (2011)
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Deng, J., Yang, L., Cheng, X., Liu, W. (2014). Self-tuning PID-type Fuzzy Adaptive Control for CRAC in Datacenters. In: Li, D., Chen, Y. (eds) Computer and Computing Technologies in Agriculture VII. CCTA 2013. IFIP Advances in Information and Communication Technology, vol 419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54344-9_27
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DOI: https://doi.org/10.1007/978-3-642-54344-9_27
Publisher Name: Springer, Berlin, Heidelberg
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