Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 48, Issue 9, Pages 2670-2682Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2017.2748418
Keywords
Adaptive control; deadzone; neural network (NN); robotic manipulator
Categories
Funding
- National Natural Science Foundation of China [61522302, 61761130080, 61573147, 91520201, 61625303]
- Beijing Natural Science Foundation [4172041]
- Fundamental Research Funds for the China Central Universities of USTB [FRF-BD-16-005A, FRF-TP-15-005C1]
Ask authors/readers for more resources
This paper addresses the problem of robotic manipulators with unknown deadzone. In order to tackle the uncertainty and the unknown deadzone effect, we introduce adaptive neural network (NN) control for robotic manipulators. State-feedback control is introduced first and a high-gain observer is then designed to make the proposed control scheme more practical. One radial basis function NN (RBFNN) is used to tackle the deadzone effect, and the other RBFNN is also proposed to estimate the unknown dynamics of robot. The proposed control is then verified on a two-joint rigid manipulator via numerical simulations and experiments.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available