Name
Title | ||
|---|---|---|
Adaptive neural network algorithm for control design of rigid-link electrically driven robots |
Abstract | ||
|---|---|---|
In this article, an adaptive neural network algorithm is developed for control issue of rigid-link electrically-driven (RLED) robot systems. First, an virtual control algorithm is designed to deal with the mechanical dynamics. Next, an actual neural network controller is used to handle the uncertainty in the mechanical and electrical dynamics. The stability is guaranteed by using a rigid stability proof. Finally, a simulation is given to show the effectiveness of the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.neucom.2007.02.012 | Neurocomputing |
Keywords | Field | DocType |
adaptive control,neural network,radial basis function | Radial basis function network,Radial basis function,Physical neural network,Computer science,Control theory,Probabilistic neural network,Time delay neural network,Artificial intelligence,Adaptive control,Robot,Artificial neural network,Machine learning | Journal |
Volume | Issue | ISSN |
71 | 4-6 | 0925-2312 |
Citations | PageRank | References |
12 | 0.68 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Su-Nan Huang | 1 | 505 | 61.65 |
| Kok Kiong Tan | 2 | 923 | 99.57 |
| Tong Heng Lee | 3 | 3489 | 279.54 |