Suitability of Artificial Neural Network for MEMS-based Flow Control

Author

Couchot, Jean-françois ; Deschinkel, Karine ; Salomon, Michel

Author_Institution

FEMTO-ST Intitute, Univ. of Fanche-Comte, Belfort, France

fYear

2012

fDate

2-3 April 2012

Firstpage

1

Lastpage

6

Abstract

These last years several research works have studied the application of Micro-Electro-Mechanical Systems (MEMS) for aero dynamical active flow control. Controlling such MEMS-based systems remains a challenge. Among the several existing control approaches for time varying systems, many of them use a process model representing the dynamic behavior of the process to be controlled. The purpose of this paper is to study the suitability of an artificial neural network first to predict the flow evolution induced by MEMS, and next to optimize the flow w.r.t a numerical criterion.

Keywords

computational fluid dynamics; flow control; micromechanical devices; neural nets; time-varying systems; turbulence; CFD; MEMS-based flow control; aero dynamical active flow control; artificial neural network; dynamic behavior; micro-electro-mechanical systems; time varying systems; Actuators; Biological neural networks; Computational modeling; Force; Micromechanical devices; Neurons; Training; CFD; MEMs; active control; neural network; real-time; turbulent flow;

fLanguage

English

Publisher

ieee

Conference_Titel

Design, Control and Software Implementation for Distributed MEMS (dMEMS), 2012 Second Workshop on

Conference_Location

Besancon

Print_ISBN

978-1-4673-1203-5

Type

conf

DOI

10.1109/dMEMS.2012.17

Filename

6195427