Fast Self-Learning of Turbulence Feedback Laws Using Gradient-Enriched Machine Learning Control-Reference-Cited by-同舟云学术

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Fast Self-Learning of Turbulence Feedback Laws Using Gradient-Enriched Machine Learning Control

Published:2024-07-14 Issue: Volume:2 Page:495-498
ISSN:
Container-title:Proceedings of the Genetic and Evolutionary Computation Conference Companion
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Author:

Cornejo Maceda Guy Y.¹^ORCID,Jiang Zhutao¹^ORCID,Lusseyran François²^ORCID,Noack Bernd R.¹³^ORCID

Affiliation:

1. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen, China

2. Laboratoire interdisciplinaire des sciences du numérique, Orsay, France

3. Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics, Harbin Institute of Technology, Shenzhen, Shenzhen, China

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Shenzhen Science and Technology Program

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3638530.3654395

Reference17 articles.

1. Space-time aspects of a three-dimensional multi-modulated open cavity flow

2. M. Brameier and W. Banzhaf. 2006. Linear Genetic Programming. Springer New York NY.

3. Closed-Loop Turbulence Control: Progress and Challenges

4. Machine-learning flow control with few sensor feedback and measurement noise

5. Stabilization of the fluidic pinball with gradient-enriched machine learning control

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