Neurointerface Using an Online Feedback-Error Learning Based Neural Network for Nonholonomic Mobile Robots

  • Lee, Hyun-Dong (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University) ;
  • Watanabe, Keigo (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University) ;
  • Jin, Sang-Ho (Department of Mechanical Engineering, Doowon Technical College) ;
  • Syam, Rafiuddin (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University) ;
  • Izumi, Kiyotaka (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University)
  • Published : 2005.06.02

Abstract

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.

Keywords