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Variable structure TITO fuzzy-logic controller implementation for a solar air-conditioning system

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  • Lygouras, J.N.
  • Kodogiannis, V.S.
  • Pachidis, Th.
  • Tarchanidis, K.N.
  • Koukourlis, C.S.

Abstract

The design and implementation of a Two-Input/Two-Output (TITO) variable structure fuzzy-logic controller for a solar-powered air-conditioning system is described in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. The first affects the temperature in the generator of the solar air-conditioner, while the second, the pressure in the power loop. The difficulty of Multi-Input/Multi-Output (MIMO) systems control is how to overcome the coupling effects among each degree of freedom. First, a traditional fuzzy-controller has been designed, its output being one of the components of the control signal for each DC motor driver. Secondly, according to the characteristics of the system's dynamics coupling, an appropriate coupling fuzzy-controller (CFC) is incorporated into a traditional fuzzy-controller (TFC) to compensate for the dynamic coupling among each degree of freedom. This control strategy simplifies the implementation problem of fuzzy control, but can also improve the control performance. This mixed fuzzy controller (MFC) can effectively improve the coupling effects of the systems, and this control strategy is easy to design and implement. Experimental results from the implemented system are presented.

Suggested Citation

  • Lygouras, J.N. & Kodogiannis, V.S. & Pachidis, Th. & Tarchanidis, K.N. & Koukourlis, C.S., 2008. "Variable structure TITO fuzzy-logic controller implementation for a solar air-conditioning system," Applied Energy, Elsevier, vol. 85(4), pages 190-203, April.
    • Handle: RePEc:eee:appene:v:85:y:2008:i:4:p:190-203
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    References listed on IDEAS

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    1. Papadopoulos, A. M. & Oxizidis, S. & Kyriakis, N., 2003. "Perspectives of solar cooling in view of the developments in the air-conditioning sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 7(5), pages 419-438, October.
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    Cited by:

    1. Spandagos, Constantine & Ng, Tze Ling, 2018. "Fuzzy model of residential energy decision-making considering behavioral economic concepts," Applied Energy, Elsevier, vol. 213(C), pages 611-625.
    2. Bulut, Hüsamettin & Aktacir, Mehmet Azmi, 2011. "Determination of free cooling potential: A case study for Istanbul, Turkey," Applied Energy, Elsevier, vol. 88(3), pages 680-689, March.
    3. Huang, Yanjun & Khajepour, Amir & Ding, Haitao & Bagheri, Farshid & Bahrami, Majid, 2017. "An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 188(C), pages 576-585.
    4. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    5. Puviyarasi, B. & Murukesh, C., 2023. "Design and implementation of Adaptive Mixed Fuzzy Controller for MIMO nonlinear systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 71-91.

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