Adaptive composite neural network disturbance observer-based dynamic surface control for electrically driven robotic manipulators-Reference-Cited by-同舟云学术

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Adaptive composite neural network disturbance observer-based dynamic surface control for electrically driven robotic manipulators

Published:2020-10-06 Issue:11 Volume:33 Page:6197-6211
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Peng Jinzhu^ORCID,Ding Shuai,Dubay Rickey

Funder

National Natural Science Foundation of China

Program for Science & Technology Innovation Talents in Universities of Henan Province

Training Plan for University’s Young Backbone Teachers of Henan Province

Outstanding Foreign Scientists Support Project in Henan Province of China

China Scholarship Council

Harrison McCain Visiting Professor Award in the University of New Brunswick

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-020-05391-8.pdf

Reference50 articles.

1. Middletone RH, Goodwin GC (1986) Adaptive computed torque control for rigid link manipulators. In: 25th IEEE conference on decision and control, Athens, Greece, pp 68–73

2. Song Z, Yi J, Zhao D, Li X (2005) A computed torque controller for uncertain robotic manipulator systems: fuzzy approach. Fuzzy Sets Syst 154:208–226

3. Peng J, Wang J, Wang Y (2011) Neural network based robust hybrid control for robotic system: an $$H_\infty $$ approach. Nonlinear Dyn 65(4):421–431

4. Sun T, Pei H, Pan Y, Zhou H, Zhang C (2011) Neural network-based sliding mode adaptive control for robot manipulators. Neurocomputing 74(14–15):2377–2384

5. Peng J, Liu Y, Wang J (2014) Fuzzy adaptive output feedback control for robotic systems based on fuzzy adaptive observer. Nonlinear Dyn 78(2):789–801

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