Name
Abstract | ||
|---|---|---|
This brief presents a systematic approach for the design of sparse dynamic output feedback control structures. A supplementary complexity cost function term is used to promote sparsity in the structure while optimizing an H 2 performance cost simultaneously. Optimization problems in which a combinatorial sparsity measure is combined with a nonlinear performance cost function are NP-hard. NP-hard problems do not have tractable solutions, requiring either a numerical solution or a relaxation into a solvable form. Relaxations will introduce conservatism, but at the same time retain stability and performance guarantees. In this brief, a new relaxation methodology is proposed, which allows the problem to be formulated as a convex semidefinite program. This is made possible via use of a new state-space form that establishes a direct relationship between the state-space and the resulting transfer function matrix parameters. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TCST.2015.2468598 | IEEE Trans. Contr. Sys. Techn. |
Keywords | Field | DocType |
Optimization,Transfer functions,Sparse matrices,Performance analysis,Minimization,Signal processing | Signal processing,Mathematical optimization,Nonlinear system,Computer science,Control theory,Regular polygon,Minification,Transfer function,Optimization problem,Sparse matrix,Semidefinite programming | Journal |
Volume | Issue | ISSN |
24 | 3 | 1063-6536 |
Citations | PageRank | References |
2 | 0.40 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Babazadeh | 1 | 15 | 3.94 |
| Amin Nobakhti | 2 | 79 | 11.97 |