Air conditioner is an essential appliance to provide human comfort environment for individual needs. For a tropical country, Malaysia has temperature fluctuation between 29 ˚C to 34 ˚C and humidity in range of 70% to 90%, air conditioner is essentially used to achieve user comforts particularly thermal comfort. However, satisfying the needs of human comfort by using air conditioner often cause the over-consumption of energy due to lack of use of intelligent and efficient control. The traditional air conditioners are typically run at constant and fixed speed has limited options to control conditioned air temperature at reduced energy consumption and achieving human thermal comfort of conditioned space. In this study, the physical parameters of Fanger’s model and Predicted Mean Vote (PMV) are used to design an innovative air conditioner controller, which is adaptively controlled by fuzzy logic to drive both fan and cooler speed by taking consideration of cooling effect of air flow variation. With the developed algorithm and controller prototype, energy consumption is optimised or minimised for the best financial outcome without sacrifice of human comfort. To validate the performance of the proposed model, the results from both microcontroller prototype and MATLAB simulation are compared for validation purpose. It has shown that both results exhibits less than 1% performance deviation in terms of computation and the potential of energy saving up to 49%