首页 /研究 /Practical point stabilization of a nonholonomic mobile robot using neural networks
LEARNING

Practical point stabilization of a nonholonomic mobile robot using neural networks

Rafael Fierro, Frank L. Lewis

发表年份
2002
引用次数
38

摘要

A control structure that makes possible the integration of a kinematic controller and a neural network (NN) computed-torque controller for nonholonomic mobile robots is presented. This control algorithm is applied to the practical point stabilization problem i.e. stabilization to a small neighborhood of the origin. The NN controller proposed in this work can deal with unmodelled bounded disturbances and/or unstructured unmodelled dynamics in the vehicle. Online NN weight tuning algorithms that do not require off-line learning yet guarantee small tracking errors and bounded control signals are utilized.

关键词

Control theory (sociology)Nonholonomic systemMobile robotBounded functionController (irrigation)Artificial neural networkComputer scienceKinematicsRobotPoint (geometry)

相关论文

查看 LEARNING 分类全部论文