Name
Abstract | ||
|---|---|---|
This paper proposes a novel velocity observer which uses neural network and sliding mode for unknown mechanical systems. The neural observer in this paper has two stages: 1) a dead-zone neural observer assures that the observer error is bounded and 2) a super-twisting second-order sliding-mode is used to guarantee finite time convergence of the observer. With sliding mode compensation, the two-sta... |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TCSII.2008.2001962 | IEEE Transactions on Circuits and Systems II: Express Briefs |
Keywords | Field | DocType |
Mechanical systems,Convergence,Neural networks,Uncertainty,Friction,Robustness,Upper bound,Control theory,Steady-state,Acceleration | State observer,Convergence (routing),Alpha beta filter,Control theory,Control engineering,Artificial neural network,Observer (quantum physics),Mathematics,Mechanical system,Finite time,Bounded function | Journal |
Volume | Issue | ISSN |
55 | 10 | 1549-7747 |
Citations | PageRank | References |
8 | 0.60 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan Resendiz | 1 | 8 | 0.60 |
| Wen Yu | 2 | 283 | 22.70 |
| Leonid M. Fridman | 3 | 1999 | 211.93 |