Interval Type 2 Adaptive Neuro-Fuzzy Inference System-Based Artificial Pacemaker Design and Stability Analysis

Abstract

This paper presents the design and simulation of an Interval type 2 fuzzy system (IT2FS) based, adaptive neuro-fuzzy inference system (ANFIS) pacemaker controller in MATLAB. After designing the type 1 fuzzy logic model, the stability of the designed system has been verified in the time-domain (unit step response). In previous works, the type 1 (IT1FS) model step response was analyzed. They are compared with the other proportional integral derivative (PID) and fuzzy models that only least-square-estimation and the backpropagation algorithms are used for tuning membership functions (MF) and generation of type 1 fis (fuzzy inference system) file. At current work, fuzzy C means (FCM) method shows better results than other methods have been used. The pacemaker controller determines the pacing rate and adjusts the heart rate of the patient for the reference input signal. The rise-time, overshoot and settling-time have been improved significantly.