A compensating scheme for robot tracking based on neural networks
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 199-206 |
| Journal / Publication | Robotics and Autonomous Systems |
| Volume | 15 |
| Issue number | 3 |
| Publication status | Published - Aug 1995 |
| Externally published | Yes |
Link(s)
Abstract
This paper considers tracking control of robots in joint space. A new control scheme is proposed based on the well-known computed torque method and a neural network based, compensating controller. This scheme takes advantages of the model based control approach and uses the neural network controller to compensate for the robot modelling uncertainties. The neural network is trained on line based on Lyapunov theory and thus its convergence is guaranteed. Simulation results are provided to demonstrate performance of the scheme. © 1995.
Research Area(s)
- Computed torque method, Convergence, Neural networks, Robots, Tracking control
Citation Format(s)
A compensating scheme for robot tracking based on neural networks. / Feng, Gang.
In: Robotics and Autonomous Systems, Vol. 15, No. 3, 08.1995, p. 199-206.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
