Predict and Analysis of the Full-Wave Rectifier Circuit With Fuzzy Modeling Technique Based on Performances of Different Membership Functions

Abstract

In the present study, A neuro-fuzzy modelling technique was used to predict and simulation the full-wave rectifier circuit. Structure of the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) was improved and trained in MATLAB toolbox. A hybrid learning algorithm consists of back-propagation and least-squares, and the real hardware data were used for training the ANFIS network. Efficiency of the developed ANFIS modelling techniques with different membership functions (MFs) was tested and a mean 99.999% recognition success was obtained. Furthermore, the full-wave rectifier circuit was simulated with the HSPICE simulation program for testing the simulation speed of ANFIS and HSPICE. The comparison between ANFIS and HSPICE indicates the feasibility and accuracy of the proposed neuro-fuzzy modelling technique. The results showed that the proposed ANFIS simulation has much higher speed and accuracy in comparison with HSPICE simulation. The neuro-fuzzy modelling technique can be simply used in software tools for designing and simulation of the full-wave rectifier circuit and the other electronic circuit. © Sila Science.