journal article·2007-10

Optimization of Piezoelectric Actuator Configuration on a Flexible Fin for Vibration Control using Genetic Algorithms

Andrew A. Rader, Fred F. Afagh, Aghil Yousefi-Koma, David G. Zimcik

Publisher page

Abstract

This study presents a novel approach to optimizing the configuration of piezoelectric actuators for vibration control of a flexible aircraft fin. The fitness (cost) function for optimization using a genetic algorithm is derived directly from the frequency response function (FRF) obtained from a finite element model of the fin. In comparison to existing approaches, this method allows optimization on much more complex geometries where the derivation of an analytical fitness function is prohibitive or impossible. This technique is applied to two optimization problems for vibration control of the fin. First, the position of a single actuator is optimized anywhere within a judiciously pre-determined area of the fin using a genetic algorithm for polynomial surface fitting of the FRF in order to obtain a continuous fitness function. Next, the configuration of a pre-determined number of up to 48 separate actuators is optimized within the same area. The optimization approach is verified against experimental results obtained from a set of 12 actuators fixed to an experimental model of the fin.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Aeroelasticity and Vibration Control · Topology Optimization in Engineering · Heat Transfer and Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON, K1S 5B6, Canada

Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON, K1S 5B6, Canada,

School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran

Institute for Aerospace Research, National Research Council of Canada, Ottawa, ON, K1A 0R6, Canada

References (32)

Show source-provided references
1. Baier, H.
2. 10.2514/3.1202710.2514/3.12027 ↗
3. 10.1177/1045389X0404279810.1177/1045389X04042798 ↗
4. 10.1109/TMECH.2003.80913110.1109/TMECH.2003.809131 ↗
5. Cook, A.M.
6. 10.1117/12.47520810.1117/12.475208 ↗
7. Goldberg, D. · Optimization, and Machine Learning · 1989
8. 10.1109/TCSI.2002.80750310.1109/TCSI.2002.807503 ↗
9. Gulsen, M.
10. 10.1088/0964-1726/8/2/01210.1088/0964-1726/8/2/012 ↗
11. 10.1177/10453890303801910.1177/104538903038019 ↗
12. Karr, C. · Design, and Process Control · 1993
13. 10.1016/0952-1976(94)00064-T10.1016/0952-1976(94)00064-T ↗
14. 10.1177/1045389X0504668610.1177/1045389X05046686 ↗
15. 10.1177/1045389X0303494010.1177/1045389X03034940 ↗
16. Kwak, M.
17. 10.1106/M2JN-6W7Y-WNVD-E6HW10.1106/M2JN-6W7Y-WNVD-E6HW ↗
18. Lopes, V. · 2004
19. 10.1177/107754630505577410.1177/1077546305055774 ↗
20. Matlab Mathworks Website (2004). Evaluating the Goodness of Fit, Curve Fitting Toolbox.
21. Moed, M.C.
22. 10.1017/S000192400001208210.1017/S0001924000012082 ↗
23. 10.1088/0964-1726/12/5/30410.1088/0964-1726/12/5/304 ↗
24. Rader, A.
25. Rader, A.
26. Rahmoune, M.
27. Ryall, T.G.
28. 10.2514/2.151910.2514/2.1519 ↗
29. 10.1088/0964-1726/10/4/30610.1088/0964-1726/10/4/306 ↗
30. Yousefi-Koma, A.
31. Yousefi-Koma, A.
32. Yousefi-Koma, A.