Fuzzy Mamdani performance water chiller control optimization using fuzzy adaptive neuro fuzzy inference system assisted

Abstract

Fuzzy Mamdani knows as one of the modern control systems. It was known to have a better performance result when compared to conventional methods. However, because the input of this modern control system sometimes is based on human experience, therefore its performance is sometimes below the conventional one. We propose using the adaptive neuro fuzzy inference system assisted (ANFIS) approach to optimize the fuzzy Mamdani membership function input to overcome this problem. We have tested our hypotheses in water chiller applications based on microcontrollers. Even though it is still behind conventional methods to cool 200 ml water, which is 6 minutes, using fuzzy ANFIS methods, we manage to improve the speed performance in cooling water from 20 minutes to 17 minutes, which is from room temperature to just 24 ^oC.