Name
Abstract | ||
|---|---|---|
This paper applies a nonconvex bilinear matrix inequality (BMI) based approach to design a nonlinear observer that satisfies multiple performance criteria simultaneously. First, the feasibility analysis of the BMI constraint is transformed into an eigenvalue problem and the convex-concave based sequential LMI optimization method is applied to search for a feasible solution. Then, the design of the nonlinear observer is formulated as a BMI feasibility problem where the estimation error dynamics is transformed into a Lure system with a sector condition constructed from the element-wise bounds on the Jacobian matrix of the nonlinearities. Finally, a numerical example is presented to demonstrate the applicability of the proposed algorithm. |
Year | Venue | Field |
|---|---|---|
2018 | 2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC) | Bilinear matrix inequality,Nonlinear system,Jacobian matrix and determinant,Upper and lower bounds,Control theory,Computer science,Matrix decomposition,Nonlinear observer,Eigenvalues and eigenvectors |
DocType | ISSN | Citations |
Conference | 0743-1619 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Wang | 1 | 11 | 2.60 |
| Rajesh Rajamani | 2 | 458 | 88.34 |
| Ali Zemouche | 3 | 235 | 27.91 |