A genetic rule weighting and selection process for fuzzy control of heating, ventilating and air conditioning systems

In this paper, we propose the use of weighted linguistic fuzzy rules in combination with a rule selection process to develop accurate fuzzy logic controllers dedicated to the intelligent control of heating, ventilating and air conditioning systems concerning energy performance and indoor comfort requirements. To do so, a genetic optimization process considering an efficient approach to perform rule weight derivation and rule selection is developed. This allows the tuning of the system to be developed at the rule level. The proposed technique was tested considering a physical modelization of a real test site.