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A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

Ning Tan Peng Yu Zhiyan Zhong Fenglei Ni

自动化学报（英文版）2022，Vol.9Issue(10)：1778-1791,14.

自动化学报（英文版）2022，Vol.9Issue(10)：1778-1791,14.DOI:10.1109/JAS.2022.105869

A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

Ning Tan ¹Peng Yu ¹Zhiyan Zhong ²Fenglei Ni³

作者信息

1. School of Computer Science and Engineering&Key Laboratory of Machine Intelligence and Advanced Computing,Ministry of Education,Sun Yat-sen University,Guangzhou 510006,China
2. School of Automation,Guangdong Polytechnic Normal University,Guangzhou 510665,China
3. State Key Laboratory of Robotics and Systems,Harbin Institute of Technology(HIT),Harbin 150080,China
折叠

摘要

关键词

Dual zeroing neural networks(ZNN)/finite-time convergence/model-free/robot control/robustness analysis

Key words

Dual zeroing neural networks(ZNN)/finite-time convergence/model-free/robot control/robustness analysis

引用本文复制引用

Ning Tan,Peng Yu,Zhiyan Zhong,Fenglei Ni..A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models[J].自动化学报（英文版）,2022,9(10):1778-1791,14.

基金项目

This work was partially supported by the National Natural Science Foundation of China(62173352,62103112),the Guangdong Basic and Applied Basic Research Foundation(2021A1515012314),the Open Project of Shenzhen Institute of Artificial Intelligence and Robotics for Society(AC01202005006),and the Key-Area Research and Development Program of Guangzhou(202007030004). （62173352,62103112）

自动化学报（英文版）

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ISSN：2329-9266

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