Optimizing MIMO control for fluidic pinball using machine learning

Created by W.Langdon from gp-bibliography.bib Revision:1.4910

@InProceedings{Cornejo:2018:GAMM,

• author = "Guy Yoslan {Cornejo Maceda} and Francois Lusseyran and Bernd R. Noack and Marek Morzynski",
• title = "Optimizing {MIMO} control for fluidic pinball using machine learning",
• booktitle = "89th GAMM Annual Meeting",
• year = "2018",
• address = "Munich, Germany",
• month = "19-23 " # mar,
• organisation = "TUM",
• keywords = "genetic algorithms, genetic programming",
• bibsource = "OAI-PMH server at api.archives-ouvertes.fr",
• oai = "oai:HAL:hal-01856252v1",
• identifier = "hal-01856252",
• language = "en",
• URL = "https://hal.archives-ouvertes.fr/hal-01856252",
• abstract = "We are looking for wake stabilization in a multi input multi output (MIMO) configuration.The wake results from an obstacle made by three cylinders in an incoming flow. The meansof action are the cylinders rotation and the output is the velocity taken downstream. Previousstudies have shown that high and low frequency forcing stabilize the wake, revealing the nonlinearinteractions. Linear control being not applicable in our case we are looking for an optimal controllaw regarding drag reduction using genetic programming, a model free MLC approach. Geneticprogramming can explore a broad spectrum of laws, exploiting the nonlinearities, ranging fromopen loop control to closed loop control.",
• notes = "LIMSI-CNRS https://jahrestagung.gamm-ev.de/index.php/2018/2018-annual-meeting https://www.events.tum.de/frontend/index.php?page_id=2083&v=AuthorList&do=17&day=244&entity_id=22304",

}

Genetic Programming entries for Guy Yoslan Cornejo Maceda Francois Lusseyran Bernd R Noack Marek Morzynski

Citations