Tracking control of mobile robot using ANFIS

Abstract

This study addresses a nonlinear trajectory tracking control problem for a kinematics Model of nonholonomic mobile robot with considering next 2 time path curvature. The tracking control of mobile robot using two cascade controllers is presented. The first fuzzy controller produces a variable which shows curvature of the path and is considered as one of the inputs of the second fuzzy controller. Adaptive Neuro Fuzzy Inference System (ANFIS) is applied as second stage controller for the solution of the path tracking problem of mobile robots. The inputs value to fuzzy logic layer are V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</sub> , C, dR & dθ the robot current linear velocity, trajectory curvature, distance from the robot actual position to the next desired position, and difference between the angles of the dθ and the robot actual heading, respectively. A gradient descent learning algorithm is used to adjust the parameters. That present controller is compared with previous work to confirm its effectiveness.