Name
Abstract | ||
|---|---|---|
This paper considers robust performance analysis and state feedback design for systems with time-varying parameter uncertainties. The notion of a strongly robust
H
∞ performance criterion is introduced, and its applications in robust performance analysis and synthesis for nominally linear systems with time-varying uncertainties are discussed and compared with the constant scaled small gain criterion. It is shown that most robust performance analysis and synthesis problems under this strongly robust ∞ performance criterion can be transformed into linear matrix inequality problems, and can be solved through finite-dimensional convex programming. The results are in general less conservative than those using small gain type criteria. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1016/0005-1098(94)00065-Q | Automatica |
Keywords | Field | DocType |
Robust control,state feedback,convex programming | Mathematical optimization,Linear system,Control theory,Control system,Robust control,State space,Convex optimization,Mathematics,Linear matrix inequality | Journal |
Volume | Issue | ISSN |
31 | 2 | 0005-1098 |
Citations | PageRank | References |
18 | 3.92 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kemin Zhou | 1 | 372 | 59.31 |
| Pramod P. Khargonekar | 2 | 690 | 198.69 |
| Jakob Stoustrup | 3 | 274 | 52.57 |
| Hans Henrik Niemann | 4 | 32 | 10.85 |