Learning to Update Engine Models with Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Learning to Update Engine Models with Deep Reinforcement Learning

Published:2023-06-23 Issue: Volume: Page:
ISSN:
Container-title:2023 6th International Symposium on Autonomous Systems (ISAS)
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Author:

Yu RuoYan¹,Li Bei¹,Shi SuMu¹,Peng Cong¹,Zhou YuNan²,Du XiangYu²

Affiliation:

1. Nanjing University of Aeronautics and Astronautics,School of Automation,Nanjing,China

2. Nanjing Engineering Institute of Aircraft Systems,Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration,Nanjing,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10164121/10164123/10164344.pdf?arnumber=10164344

Reference26 articles.

1. Reinforcement learning:an introduction;sutton,2018

2. Calibration and Uncertainty Quantification of Gas Turbine Performance Models

3. Reinforcement learning for control: Performance, stability, and deep approximators,Annual Reviews in Control;bu?oniu,2018

4. H ? model-free reinforcement learning with robust stability guarantee;han;arXiv preprint arXiv 1911 06912,2019

5. On Particle Methods for Parameter Estimation in State-Space Models

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