Adaptive Neuro-fuzzy Network Control for a Mobile Robot

被引：9
|
作者：
Jang, Jun Oh [1 ]
机构：
[1] Uiduk Univ, Dept Comp Control Engn, Kyongju 780713, South Korea
来源：
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | 2011年 / 62卷 / 3-4期
关键词：
Mobile robot; Neuro-fuzzy networks; Lyapunov stability; Feedback control; DESIGN; IMPLEMENTATION;
D O I：
10.1007/s10846-010-9453-4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A control structure that makes possible the integration of a kinematic controller and a neuro-fuzzy network (NFN) dynamic controller for mobile robots is presented. A combined kinematic/dynamic control law is developed using backstepping and stability is guaranteed by Lyapunov theory. The NFN controller proposed in this work can deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamic in the mobile robot. On-line NFN parameter tuning algorithms do no require off-line learning yet guarantee small tracking errors and bounded control signals are utilized.
引用
收藏
页码：567 / 586
页数：20
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