Genetic-algorithm-optimized fuzzy logic control of a variable air volume air-conditioning system

An improved intelligent control strategy based on fuzzy logic reasoning was presented in order to conserve energy while improving indoor thermal comfort for A Variable air volume (VAV) air-conditioning system. Predicted Mean Vote (PMV) index was incorporated into the control strategy to assess thermal comfort level. An optimization program based on Genetic Algorithm (GA) was developed with C language to extract the optimal scaling factors and control rules for the Fuzzy Logic Controller (FLC). Both the optimized and un-optimized FLCs were tested with VAV operation mode in an artificial environment laboratory. The results indicate that the un-optimized and GA-optimized FLC are capable of saving energy by 13% and 24% respectively while improving the thermal comfort level considerably compared with the conventional PID control.