@inproceedings{7e3b4b9b6f384d4aa86db4ccd544c7b0,
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.",
keywords = "Dynamics, Kinematics, RBF, Spherical robot, Trajectory tracking",
author = "Minghui Zheng and Qiang Zhan and Jinkun Liu and Cai Yao",
year = "2012",
doi = "10.4028/www.scientific.net/AMR.383-390.631",
language = "英语",
isbn = "9783037852958",
series = "Advanced Materials Research",
pages = "631--637",
booktitle = "Manufacturing Science and Technology",
note = "2011 International Conference on Manufacturing Science and Technology, ICMST 2011 ; Conference date: 16-09-2011 Through 18-09-2011",
}