Adaptive Neural Tracking Control of Robotic Manipulators with Guaranteed NN Weight Convergence
Although adaptive control for robotic manipulators has been widely studied, most of them require the acceleration signals of the joints, which are usually difficult to measure directly. Although neural networks (NNs) have been used to approximate the unknown nonlinear dynamics in the robotic systems...
Saved in:
| Main Authors: | Jun Yang, Jing Na, Guanbin Gao, Chao Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/7131562 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Neural Tracking Control for a Two-Joint Robotic Manipulator with Unknown Time-Varying Delays
by: Jiayao Wang, et al.
Published: (2022-01-01) -
Adaptive Backstepping Sliding Mode Control of Trajectory Tracking for Robotic Manipulators
by: Zhu Dachang, et al.
Published: (2020-01-01) -
Adaptive Fast Nonsingular Fixed-Time Tracking Control for Robot Manipulators
by: Huihui Pan, et al.
Published: (2021-01-01) -
Robust Adaptive Tracking Control of a Class of Robot Manipulators with Model Uncertainties
by: G. Solís-Perales, et al.
Published: (2012-01-01) -
Adaptive Incremental Nonlinear Dynamic Inversion Control with Guaranteed Stability for Aerial Manipulators
by: Chanhong Park, et al.
Published: (2025-04-01)