Name
Abstract | ||
|---|---|---|
This paper concerns the design of new positive filters for positive linear systems. In fact, we propose a new positive full order filter for positive linear systems subject to unknown inputs and bounded disturbances. The designed filter is always nonnegative at any time and converges asymptotically to the real state vector. This paper is among first attempts to design positive unknown input filters (PUIF) for positive linear systems. The proposed approach is based on the unbiasedness of the estimation error and by imposing the positivity of the design parameters; then a new method to avoid the derivative of the disturbance vector in the filtering error dynamics is proposed. Based on the extended strictly positive real (ESPR) design, this problem is solved by applying the Linear Matrix Inequalities (LMI)-based ESPR Lemma. Note that all structural constraints on filter matrices are addressed in terms of LMI formulation. An algorithm that summarizes the different steps of the proposed positive filter design is given. A numerical example is finally given to illustrate the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.23919/ACC45564.2020.9147795 | 2020 AMERICAN CONTROL CONFERENCE (ACC) |
DocType | ISSN | Citations |
Conference | 0743-1619 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Montassar Ezzine | 1 | 8 | 1.39 |
| H. Souley Ali | 2 | 0 | 0.34 |
| Mohamed Darouach | 3 | 261 | 42.82 |
| Hassani Messaoud | 4 | 48 | 14.98 |