Name
Title | ||
|---|---|---|
A Robust Finite Memory Observer Design for Continuous-Discrete Linear Time-Varying Systems with Process and Measurement Noises |
Abstract | ||
|---|---|---|
In this paper, a robust finite memory observer has been developed for the continuous-discrete linear time-varying (CD-LTV) systems, which are modeled by the ordinary differential equations (ODEs) in the presence of process noise and are observed through discrete noisy measurements. The proposed method collects a finite number of noisy measurements in the most recent time window to obtained an analytical form of state estimation in the sense of least square. In the meantime, it has also been proved in this paper that the state estimation is unbiased and has the smallest dispersion among all the linear estimators. It is worth noting that the presented method converges within a finite time and shows no initial condition problem, which appears to be a significant advantage for real practical applications. The infiuence of window length has equally been demonstrated attached with a window length selection strategy. A numerical simulation example is provided at the end of this paper to verify the unbiased state estimation performance of the proposed observer via Monte Carlo simulations. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.23919/ACC50511.2021.9482866 | 2021 AMERICAN CONTROL CONFERENCE (ACC) |
DocType | ISSN | Citations |
Conference | 0743-1619 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tingting Zhang | 1 | 0 | 0.34 |
| Frédéric Kratz | 2 | 0 | 0.34 |
| Yunhui Hou | 3 | 0 | 0.34 |
| Vincent Idasiak | 4 | 0 | 0.34 |