Abstract
Four algorithms are described to search and find spatial configuration for the placement of a finite number of actuators and sensors on a continuous flexible structure to reduce deformations in the structures to a minimum in H∞ sense. The computational cost of the optimal mapping search is reduced through four techniques. First, the computationally expensive goal function based on the complete H∞ design is replaced by a two-step hybrid function, which performs a computationally inexpensive pass-fail test and proceeds to the complete H∞ design only if the test was passed. Second a target H∞ norm used in the mentioned pass-fail test is adjusted based on the already evaluated mappings in order to increase the number of failed tests and reduce the number of complete H∞ designs. Third, the exhaustive search as the basic search technique is replaced by a more intelligent genetic algorithm. Finally, the search is implemented on a parallel computer. The algorithms are benchmarked for two test cases: a model of a simply supported beam, and a model of the UCLA Large Space Structure.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the American Control Conference |
| Publisher | IEEE |
| Pages | 1812-1816 |
| Number of pages | 5 |
| Volume | 3 |
| State | Published - 1999 |
| Externally published | Yes |
| Event | Proceedings of the 1999 American Control Conference (99ACC) - San Diego, CA, USA Duration: Jun 2 1999 → Jun 4 1999 |
Other
| Other | Proceedings of the 1999 American Control Conference (99ACC) |
|---|---|
| City | San Diego, CA, USA |
| Period | 6/2/99 → 6/4/99 |
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ASJC Scopus subject areas
- Control and Systems Engineering
Cite this
Intelligent algorithms for H∞-optimal placement of actuators and sensors in structural control. / Chemishkian, Sergey; Arabyan, Ara -.
Proceedings of the American Control Conference. Vol. 3 IEEE, 1999. p. 1812-1816.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Intelligent algorithms for H∞-optimal placement of actuators and sensors in structural control
AU - Chemishkian, Sergey
AU - Arabyan, Ara -
PY - 1999
Y1 - 1999
N2 - Four algorithms are described to search and find spatial configuration for the placement of a finite number of actuators and sensors on a continuous flexible structure to reduce deformations in the structures to a minimum in H∞ sense. The computational cost of the optimal mapping search is reduced through four techniques. First, the computationally expensive goal function based on the complete H∞ design is replaced by a two-step hybrid function, which performs a computationally inexpensive pass-fail test and proceeds to the complete H∞ design only if the test was passed. Second a target H∞ norm used in the mentioned pass-fail test is adjusted based on the already evaluated mappings in order to increase the number of failed tests and reduce the number of complete H∞ designs. Third, the exhaustive search as the basic search technique is replaced by a more intelligent genetic algorithm. Finally, the search is implemented on a parallel computer. The algorithms are benchmarked for two test cases: a model of a simply supported beam, and a model of the UCLA Large Space Structure.
AB - Four algorithms are described to search and find spatial configuration for the placement of a finite number of actuators and sensors on a continuous flexible structure to reduce deformations in the structures to a minimum in H∞ sense. The computational cost of the optimal mapping search is reduced through four techniques. First, the computationally expensive goal function based on the complete H∞ design is replaced by a two-step hybrid function, which performs a computationally inexpensive pass-fail test and proceeds to the complete H∞ design only if the test was passed. Second a target H∞ norm used in the mentioned pass-fail test is adjusted based on the already evaluated mappings in order to increase the number of failed tests and reduce the number of complete H∞ designs. Third, the exhaustive search as the basic search technique is replaced by a more intelligent genetic algorithm. Finally, the search is implemented on a parallel computer. The algorithms are benchmarked for two test cases: a model of a simply supported beam, and a model of the UCLA Large Space Structure.
UR - http://www.scopus.com/inward/record.url?scp=0033283479&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0033283479&partnerID=8YFLogxK
M3 - Conference contribution
VL - 3
SP - 1812
EP - 1816
BT - Proceedings of the American Control Conference
PB - IEEE
ER -