Human–machine interaction controller of upper limb based on iterative learning method with zeroing neural algorithm and disturbance observer-Reference-Cited by-同舟云学术

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Human–machine interaction controller of upper limb based on iterative learning method with zeroing neural algorithm and disturbance observer

Published:2023-06 Issue: Volume:122 Page:106108
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Chai Yuanyuan,Liu Keping,Duan Xiaoqin,Yi Jiang,Sun Ruiling,Li Jiacong

Funder

Changsha Science and Technology Project

Science and Technology Projects of Fujian Province

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference38 articles.

1. A deep autoencoder trust model for mitigating jamming attack in IoT assisted by cognitive radio;Abdalzaher;IEEE Syst. J.,2022

2. Comparative performance assessments of machine-learning methods for artificial seismic sources discrimination;Abdalzaher;IEEE Access,2021

3. A deep learning model for earthquake parameters observation in IoT system-based earthquake early warning;Abdalzaher;IEEE Internet Things J.,2022

4. Academic review and perspectives on robotic exoskeletons;Bao;IEEE Trans. Neural Syst. Rehabil. Eng.,2019

5. Trajectory tracking control for perturbed robot manipulators using iterative learning method;Bouakrif;Int. J. Adv. Manuf. Technol.,2016

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. sEMG data driven-based anti-disturbance control enables adaptive interaction of lower limb rehabilitation exoskeleton;Biomedical Signal Processing and Control;2024-08

2. A noise suppression zeroing neural network for trajectory tracking with joint angle constraints of mobile manipulator;Engineering Applications of Artificial Intelligence;2024-07

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