A Neuro-interface with fuzzy compensator for controlling nonholonomic mobile robots

Rafiuddin Syam, Keigo Watanabe, Kiyotaka Izumi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This paper describes a control method for mobile robots represented by a nonlinear dynamical system, which is subjected to an output deviation caused by drastically changed disturbances. We here propose some controllers in the framework of neuro-interface. It is assumed that a neural network (NN)-based feedforward controller is construcetd by following the concept of virtual master-slave robot, in which a virtual master robot as a feedforward controller is used to control the slave (i.e., actual) robot. The whole system of the present neuro-interface consists of an NN-based feedforward controller, a feedback PD controller and an adaptive fuzzy feedback compensator. The NN-based feedforward controller is trained offline by using a gradient method, the gains of the PD controller are to be chosen constant, and the adaptive fuzzy compensator is constructed with a simplified fuzzy reasoning. Some simulations are presented to confirm the validity of the present approach, where a nonholonomic mobile robot with two independent driving wheels is assmued to have a disturbance due to the change of mass for the robot.

Original languageEnglish
Pages (from-to)449-461
Number of pages13
JournalNeural Computing and Applications
Issue number5-6
Publication statusPublished - Oct 1 2008
Externally publishedYes


  • Disturbances
  • Fuzzy compensator
  • Neuro-interface
  • Nonholonomic mobile robots

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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