Adaptive NN-Based Tracking Control for Partial Uncertain Time-Delayed WMR System

被引：0
|
作者：
Ding, Liang [1 ]
Li, Shu [1 ]
Gao, Haibo [1 ]
Gao, Ying [2 ]
Deng, Zongquan [1 ]
机构：
[1] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150001, Heilongjiang, Peoples R China
[2] Tangshan Normal Univ, Dept Math & Informat Sci, Tangshan 063000, Hebei, Peoples R China
来源：
PROCEEDINGS OF 2018 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE RCAR) | 2018年
基金：
中国国家自然科学基金;
关键词：
Adaptive control; neural network; partial time delay; wheeled mobile robot; Lyapunov function; NEURAL-NETWORK CONTROL; NONLINEAR-SYSTEMS; MOBILE ROBOT; STATE;
D O I：
暂无
中图分类号：
TP24 [机器人技术];
学科分类号：
080202 ; 1405 ;
摘要：
In this paper, an adaptive neural network (NN) -based tracking control algorithm is proposed for the partial uncertain state time-delayed wheeled mobile robotic (WMR) system with. By using the backstepping method, and the appropriate Lyapunov-Krasovskii functionals, a suitable adaptive controllers is designed for the WMR system such that 1) eliminate the influence of partial uncertain time delay on system stability; 2) ensure all signals in WMR system to be bounded; 3) guarantee the robot can track the desired trajectory with the error convergence to a compact set by zero. The numerical simulation results verify the performance of the proposed control algorithm.
引用
收藏
页码：118 / 123
页数：6
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