Name
Abstract | ||
|---|---|---|
A robust identification-based state derivative estimation method for uncertain nonlinear systems is developed. The identifier architecture consists of a recurrent multilayer dynamic neural network which approximates the system dynamics online, and a continuous robust feedback Robust Integral of the Sign of the Error (RISE) term which accounts for modeling errors and exogenous disturbances. Numerical simulations provide comparisons with existing robust derivative estimation methods including: a high gain observer, a 2-sliding mode robust exact differentiator, and numerical differentiation methods, such as backward difference and central difference. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TAC.2012.2203452 | IEEE Trans. Automat. Contr. |
Keywords | Field | DocType |
Robustness,Observers,Stability analysis,Convergence,Noise,Nonlinear systems | Numerical differentiation,Convergence (routing),Mathematical optimization,Nonlinear system,Control theory,Differentiator,Finite difference,Robustness (computer science),System dynamics,Robust control,Mathematics | Journal |
Volume | Issue | ISSN |
58 | 1 | 0018-9286 |
Citations | PageRank | References |
4 | 0.42 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shubhendu Bhasin | 1 | 167 | 17.89 |
| R. Kamalapurkar | 2 | 367 | 26.14 |
| Huyen T. Dinh | 3 | 58 | 3.00 |
| Warren E. Dixon | 4 | 1757 | 149.42 |