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Performance of hybrid optimization methods applied to active flow control devices

Author
Coma, M.; Tousi, N.; Pons-Prats, J.; Bergadà, J.M.; Bugeda, G.
Type of activity
Presentation of work at congresses
Name of edition
AeroBest 2021
Date of publication
2021
Presentation's date
2021-07-23
Book of congress proceedings
AeroBest 2021 ECCOMAS Thematic Conference on Multidisciplinary Design Optimization of Aerospace Systems : programme and abstracts, 21-23 July 2021
First page
1
Last page
1
URL
https://aerobest2021.idmec.tecnico.ulisboa.pt/program/ Open in new window
Abstract
Genetic Algorithms (GA) are optimization methods that are usually very robust but have a slow convergence to the exact minimum. On the other hand, Gradient Based methods which converge better, are not so robust, and can get stuck in local minimums or flat areas. In this article a Hybrid optimization method is presented and its performance is compared against a Gradient Based method and a Genetic Algorithm. The comparison is established with a Gradient Based method, which is a Conjugate Gradient,...
Keywords
Active Flow Control, Evolutionary Techniques, Gradient-based Methods, Hybrid Optimization Methods, Optimization, Population-based Methods, Synthetic Jet
Group of research
ICARUS - Intelligent Communications and Avionics for Robust Unmanned Aerial Systems
MICROTECH LAB - Microtechnology for the Industry
RMEE - Strength of Materials and Structural Engineering Research Group
Universitat Politècnica de Catalunya

Participants