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International journal of fuzzy logic and intelligent systems : IJFIS v.9 no.2, 2009년, pp.76 - 82  
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Adaptive Fuzzy Output Feedback Control based on Observer for Nonlinear Heating, Ventilating and Air Conditioning System

Baek, Jae-Ho    (Department of Electrical and Electronics Engineering, Yonsei University   ); Hwang, Eun-Ju    (Department of Electrical and Electronics Engineering, Yonsei University   ); Kim, Eun-Tai    (Department of Electrical and Electronics Engineering, Yonsei University   ); Park, Mi-gnon    (Department of Electrical and Electronics Engineering, Yonsei University  );
  • 초록

    A Heating, Ventilating and Air Conditioning (HVAC) system is a nonlinear multi-input multi-output (MIMO) system. This system is very difficult to control the temperature and the humidity ratio of a thermal space because of complex nonlinear characteristics. This paper proposes an adaptive fuzzy output feedback control based on observer for the nonlinear HVAC system. The nonlinear HVAC system is linearized through dynamic extension. State observers are designed for estimating state variables of the HVAC system. Fuzzy systems are employed to approximate uncertain nonlinear functions of the HVAC system with unavailable state variables. The obtained controller compares with an adaptive feedback controller. Simulation is given to demonstrate the effectiveness of our proposed adaptive fuzzy method.


  • 주제어

    Adaptive Control .   Fuzzy Control .   MIMO System .   temperature control .   humidity control .   HVAC System.  

  • 참고문헌 (12)

    1. Betzaida Argello-Serrano and Miguel Vlez-Reyes, "Nonlinear Control of a Heating, Ventilating and Air Conditioning System with Thermal Load Estimation," IEEE Trans. Control Systems Technology, Vol. 7, pp. 56-63, 1999 
    2. C.P. Underwood, HVAC Control Systems : Modeling, analysis and design, E&FN SPON, 1999 
    3. Elham Semsar, Mohammad Javad Yazdanpanah and Caro Lucas, "Nonlinear Control and Disturbance Decoupling of an HVAC system via Feedback Linearization and Back-Stepping," Proceedings of IEEE Conference, Vol. 1, pp. 646-650, 2003 
    4. Ming-Li Chiang and Li-Chen Fu, "Adaptive and Robust Control for Nonlinear HVAC System," the IEEE International Conference on Systems, Man, and Cybernetics, Vol. 6, pp. 4982-4987, 2006 
    5. Rahmat Shoureshi, "Intelligent control systems : Are they for real?," Trans. ASME, Vol. 115, pp. 392-401, 1993 
    6. Alberto Isidori, Nonlinear control systems, 3rd ed, New York - Springer Verlag, 1995 
    7. N. Sheikholeslami, D. Shahmirzadi, E. Semsar, C. Lucas and M.J. Yazdanpanah, "Applying brain emotional learning algorithm for multivarizble control of HVAC systems," Journal of Intelligent and Fuzzy Systems, Vol. 17, pp. 35-46, 2006 
    8. Farzan Rashidi and Behzad Moshiri, "Design of a Robust Sliding Mode Fuzzy Controller for Nonlinear HVAC Systems," ICAISC 2004, LNAI 3070, pp. 984-989, 2004 
    9. MohammadYaqub and SyedM.Zubair, "Capacity Control for Refrigeration and Air-Conditioning Systems: A Comparative Study", Journal of Energy Resources Technology, Vol. 123, pp. 92-9, 2001 
    10. Behzad Moshiri and Farzan Rashidi, "Self-tuning Based Fuzzy PID Controllers : Application to Control of Nonlinear HVAC Systems," IDEAL, Vol. 3177, pp. 437-442, 2004 
    11. Michael J. Coffin, Direct Digital Control for Building HVAC Systems. 2nd ed. [S.l.], Kluwer Academic Publishers, 1998 
    12. Han-Xiong Li and Shaocheng Tong, "A Hybird Adaptive Fuzzy Control for A Class of Nonlinear MIMO Systems," IEEE TRANS. ON FUZZY SYST., Vol. 11, pp. 24-34, 2003 

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