Name
Abstract | ||
|---|---|---|
This paper considers the problem of designing a state-feedback control law which “minimizes” multiple quadratic performance objectives in the presence of uncertain linear plant dynamics. Vector optimization techniques are used to minimize upper-bounds on each performance objective (guaranteed-cost). By exploiting the linear uncertainty bound introduced by Bernstein (1987), the vector optimization problem is scalarized and Pareto optimal solutions are computed. The theory is applied to a numerical example with two quadratic performance measures. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1016/S0005-1098(98)00062-4 | Automatica |
Keywords | Field | DocType |
Multi-objective optimization,guaranteed-cost,state feedback,generalized algebraic Riccati equation,linear matrix inequalities | Mathematical optimization,Linear system,Control theory,Vector optimization,Quadratic equation,Multi-objective optimization,Riccati equation,Quadratic programming,Robust control,Linear matrix inequality,Mathematics | Journal |
Volume | Issue | ISSN |
34 | 10 | 0005-1098 |
Citations | PageRank | References |
2 | 0.44 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Dorato | 1 | 165 | 19.52 |
| Laura Menini | 2 | 344 | 44.96 |
| C TREML | 3 | 2 | 0.44 |