Abstract
This paper considers mixed H2/H∞ control for linear systems with structured uncertainty via convex optimization. A generalized Riccati equation and a change of multivariable technique are employed in order to convexify the design problem. The resulting convex optimization problem is shown to be reduceable to a Generalized Eigenvalue Minimization Problem.
| Original language | English |
|---|---|
| Title of host publication | American Control Conference |
| Editors | Anon |
| Place of Publication | Piscataway, NJ, United States |
| Publisher | Publ by IEEE |
| Pages | 245-247 |
| Number of pages | 3 |
| ISBN (Print) | 0780308611 |
| Publication status | Published - 1993 |
| Event | Proceedings of the 1993 American Control Conference Part 3 (of 3) - San Francisco, CA, USA Duration: 1993 Jun 2 → 1993 Jun 4 |
Other
| Other | Proceedings of the 1993 American Control Conference Part 3 (of 3) |
|---|---|
| City | San Francisco, CA, USA |
| Period | 93/6/2 → 93/6/4 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Mixed H2/H∞ control of uncertain systems. / Bambang, Riyanto; Shimemura, Etsujiro; Uchida, Kenko.
American Control Conference. ed. / Anon. Piscataway, NJ, United States : Publ by IEEE, 1993. p. 245-247.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Mixed H2/H∞ control of uncertain systems
AU - Bambang, Riyanto
AU - Shimemura, Etsujiro
AU - Uchida, Kenko
PY - 1993
Y1 - 1993
N2 - This paper considers mixed H2/H∞ control for linear systems with structured uncertainty via convex optimization. A generalized Riccati equation and a change of multivariable technique are employed in order to convexify the design problem. The resulting convex optimization problem is shown to be reduceable to a Generalized Eigenvalue Minimization Problem.
AB - This paper considers mixed H2/H∞ control for linear systems with structured uncertainty via convex optimization. A generalized Riccati equation and a change of multivariable technique are employed in order to convexify the design problem. The resulting convex optimization problem is shown to be reduceable to a Generalized Eigenvalue Minimization Problem.
UR - http://www.scopus.com/inward/record.url?scp=0027845868&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0027845868&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0027845868
SN - 0780308611
SP - 245
EP - 247
BT - American Control Conference
A2 - Anon, null
PB - Publ by IEEE
CY - Piscataway, NJ, United States
ER -