Paper Title:
Trajectory Tracking of a Spherical Robot Based on an RBF Neural Network
  Abstract

This paper deals with trajectory tracking problem of a spherical mobile robot, BHQ-1. First, a desired velocity is obtained by proposing a PD controller based on the kinematics. Then a PD controller with an RBF (Radial Basis Function) neural network is proposed based on the desired velocity and the inexact dynamics. The weights of the RBF network are designed with an adaptive rule based on the tracking error, and hence the network can compensate the uncertainties of the dynamics more effectively. Stability is presented via Lyapunov Theory and simulation results are provided to illustrate the tracking performance.

  Info
Periodical
Advanced Materials Research (Volumes 383-390)
Chapter
Chapter 1: Computer-Aided Manufacturing
Edited by
Wu Fan
Pages
631-637
DOI
10.4028/www.scientific.net/AMR.383-390.631
Citation
M. H. Zheng, Q. Zhan, J. K. Liu, Y. Cai, "Trajectory Tracking of a Spherical Robot Based on an RBF Neural Network", Advanced Materials Research, Vols. 383-390, pp. 631-637, 2012
Online since
November 2011
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Price
$32.00
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