A Simple Tuning Algorithm of Augmented Fuzzy Membership Functions

The successful application of fuzzy control depends to a large extent on the parameters of some subjective decisions, such as fuzzy membership function (MF). Fuzzy logic controller (FLC) implementing augmented output MFs as compare to input MFs is presented to improve the accuracy, robustness, and performance of the system. The best possible combination of input and output MFs is introduced to distribute the uniform input MFs and augmented output MFs in the treatise. The simulation of the 2-Inputs 1-Output Fuzzy Control System is performed in many nonlinear processes. Then, the experimental outcomes of the uniformly and augmented distributed output MFs are compared under similar circumstances. The experimental outcomes are in a virtuous covenant with the simulation outcomes. The experimental outcomes show that the root mean square error (RMSE) is reduced around 75.3% and bringing down the relative error to the acceptable range (≤±10%). The control accuracy is improved and the robustness is boosted by reducing the RMSE through the FLC with augmented-distributed output MFs. Moreover, the cost and energy efficiency in any fuzzy system will be improved by implementing the augmented-distributed output MFs using the best possible combination of input and output MFs.