Linear genetic programming control for strongly nonlinear dynamics with frequency crosstalk
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @Article{Li:2018:AM,
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author = "Ruiying Li and Bernd R. Noack and Laurent Cordier and
Jacques Boree",
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title = "Linear genetic programming control for strongly
nonlinear dynamics with frequency crosstalk",
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journal = "Archives of Mechanics",
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year = "2018",
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volume = "70",
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number = "6",
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pages = "505--534",
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publisher = "HAL CCSD",
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month = jan # "~08",
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keywords = "genetic algorithms, genetic programming, flow control,
nonlinear dynamics, turbulent wake, physics, mechanics,
mechanics of the fluids, materials and structures in
mechanics, engineering sciences, acoustics, automatic,
electromagnetism, reactive fluid environment, electric
power, thermics, vibrations",
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URL = "https://hal.archives-ouvertes.fr/hal-02290373",
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DOI = "doi:10.24423/aom.3000",
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abstract = "We advance Genetic Programming Control (GPC) for
turbulence flow control application building on the
pioneering work of [1]. GPC is a recently proposed
model-free control framework which explores and
exploits strongly nonlinear dynamics in an unsupervised
manner. The assumed plant has multiple actuators and
sensors and its performance is measured by a cost
function. The control problem is to find a control
logic which optimises the given cost function. The
corresponding regression problem for the control law is
solved by employing linear genetic programming as an
easy and simple regression solver in a high-dimensional
control search space. This search space comprises
open-loop actuation, sensor-based feedback and
combinations thereof --- thus generalizing former GPC
studies [2, 3]. This new methodology is denoted as
linear genetic programming control (LGPC). The focus of
this study is the frequency crosstalk between unforced,
unstable oscillation and the actuation at different
frequencies. LGPC is first applied to the stabilization
of a forced nonlinearly coupled three-oscillator model
comprising open- and closed-loop frequency crosstalk
mechanisms. LGPC performance is then demonstrated in a
turbulence control experiment, achieving 22 percent
drag reduction for a simplified car model. In both
cases, LGPC identifies the best nonlinear control
achieving the optimal performance by exploiting
frequency crosstalk. Our control strategy is suited to
complex control problems with multiple actuators and
sensors featuring nonlinear actuation dynamics.
Significant further performance enhancement is
envisioned in the more general field of machine
learning control [4].",
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annote = "Turbulence Incompressible et Controle (TIC ) ;
Departement Fluides, Thermique et Combustion (FTC) ;
Institut Pprime (PPRIME) ; Universite de
Poitiers-Centre National de la Recherche Scientifique
(CNRS)-ENSMA-Universite de Poitiers-Centre National de
la Recherche Scientifique (CNRS)-ENSMA-Institut Pprime
(PPRIME) ; Universite de Poitiers-Centre National de la
Recherche Scientifique (CNRS)-ENSMA-Universite de
Poitiers-Centre National de la Recherche Scientifique
(CNRS)-ENSMA; Acoustique, Aerodynamique, Turbulence
(2AT ) ; Departement Fluides, Thermique et Combustion
(FTC) ; Institut Pprime (PPRIME) ; Universite de
Poitiers-Centre National de la Recherche Scientifique
(CNRS)-ENSMA-Universite de Poitiers-Centre National de
la Recherche Scientifique (CNRS)-ENSMA-Institut Pprime
(PPRIME) ; Universite de Poitiers-Centre National de la
Recherche Scientifique (CNRS)-ENSMA-Universite de
Poitiers-Centre National de la Recherche Scientifique
(CNRS)-ENSMA",
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bibsource = "OAI-PMH server at api.archives-ouvertes.fr",
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contributor = "Turbulence Incompressible et Controle and
Aerodynamique Acoustique, Turbulence",
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description = "International audience",
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identifier = "hal-02290373",
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language = "en",
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oai = "oai:HAL:hal-02290373v1",
- }
Genetic Programming entries for
Ruiying Li
Bernd R Noack
Laurent Cordier
Jacques Boree
Citations