Name
Abstract | ||
|---|---|---|
The derivative estimation problem is addressed in this paper by using Volterra integral operators which allow to obtain the estimates of the time derivatives with fast convergence rate. A deadbeat state observer is used to provide the estimates of the derivatives with a given fixed-time convergence. The estimation bias caused by modelling error is characterised herein as well as the ISS property of the estimation error with respect to the measurement perturbation. A number of numerical examples are carried out to show the effectiveness of the proposed differentiator also including comparisons with some existing methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1080/00207179.2018.1478130 | INTERNATIONAL JOURNAL OF CONTROL |
Keywords | Field | DocType |
Linear integral operators, numerical differentiation, non-asymptotic identification, state estimation, Fredholm-Volterra integral equations | Kernel (linear algebra),Numerical differentiation,Applied mathematics,Mathematical optimization,Rate of convergence,Operator (computer programming),Derivative estimation,Mathematics | Journal |
Volume | Issue | ISSN |
91 | 9 | 0020-7179 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Li | 1 | 0 | 2.03 |
| Gilberto Pin | 2 | 136 | 17.21 |
| Giuseppe Fedele | 3 | 97 | 15.53 |
| T Parisini | 4 | 935 | 113.17 |