Adaptive neuro-fuzzy control for trajectory tracking of a wheeled mobile robot

Abstract

This paper presents a technique for autonomous mobile robot control. In recent day, computational intelligent techniques, such as artificial neural network (ANN), fuzzy inference system (FIS), and adaptive neuro-fuzzy inference system (ANFIS), are mainly considered as applicable techniques from modeling point of view. ANFIS has taken the integrate performance of neural network and fuzzy inference system. In this architecture different error coordinates χe, Ye, θe, are given as input to the adaptive fuzzy controller and output from the controller is steering angle and linear velocity for the mobile robot. Simulation experiments using MATLAB and labview demonstrate that the proposed ANFIS controller can be effectively applied to control the mobile robot safely and reach to target objects.