Energy efficiency, Fuzzy logic controllers, Genetic algorithms, HVAC, Real time control, TSK modelling, Two-variable plant
The indoor human comfort, working efficiency and health are dependent on the control of the quality of air in a heating-ventilation and air-conditioning (HVAC) system. The aim of present paper is to improve this control considering the most important variables – the air temperature, relative humidity and concentration of carbon dioxide by applying fuzzy logic and genetic algorithms (GAs) for compensation of the variables coupling and the plant nonlinearity by energy efficient control. Two fuzzy logic controllers (FLCs) are designed, one of which two-variable based on a derived modified two-variable Takagi-Sugeno-Kang (TSK) plant model. GAs off-line parameter optimization is applied in the TSK modelling and the FLCs tuning. The FLCs are programmed in MATLABTM and in an industrial programmable logic controller and applied for the real time control of the variables of a laboratory HVAC system. The short settling time and the lack of overshoot in the transient responses of the controlled variables are an evidence for the high accuracy reached and the economic control.
Cite this paper
Snejana Yordanova. (2017) Energy Efficient Fuzzy Logic Control of Indoor Air-Conditioning in Real Time. International Journal of Control Systems and Robotics, 2, 40-47