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

页码：118 / 123

页数：6

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