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Building a Self-Evolving Digital Twin System with Bayesian Optimization and Deep Reinforcement Learning for Complex Equipment Optimization and Control

Kunyu Wang Zhen Chen Lin Zhang Mohammad S.Obaidat Jin Cui Hongbo Cheng Han Lu

清华大学学报自然科学版（英文版）2026，Vol.31Issue(1)：199-216,18.

清华大学学报自然科学版（英文版）2026，Vol.31Issue(1)：199-216,18.DOI:10.26599/TST.2024.9010163

Building a Self-Evolving Digital Twin System with Bayesian Optimization and Deep Reinforcement Learning for Complex Equipment Optimization and Control

Kunyu Wang ¹Zhen Chen ²Lin Zhang ³Mohammad S.Obaidat ⁴Jin Cui ²Hongbo Cheng ²Han Lu²

作者信息

1. Hangzhou International Innovation Institute of Beihang University,Hangzhou 311115,China||School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China
2. School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China
3. Hangzhou International Innovation Institute of Beihang University,Hangzhou 311115,China||School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China||State Key Laboratory of Intelligent Manufacturing System Technology,Beijing 100854,China
4. King Abdullah Ⅱ School of Information Technology,University of Jordan,Amman 999045,Jordan
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摘要

关键词

equipment digital twin/Bayesian optimization/deep reinforcement learning(DRL)/dynamic system modeling/intelligent control

Key words

equipment digital twin/Bayesian optimization/deep reinforcement learning(DRL)/dynamic system modeling/intelligent control

引用本文复制引用

Kunyu Wang,Zhen Chen,Lin Zhang,Mohammad S.Obaidat,Jin Cui,Hongbo Cheng,Han Lu..Building a Self-Evolving Digital Twin System with Bayesian Optimization and Deep Reinforcement Learning for Complex Equipment Optimization and Control[J].清华大学学报自然科学版（英文版）,2026,31(1):199-216,18.

基金项目

This work was supported by the National Natural Science Foundation of China(No.62373026). （No.62373026）

清华大学学报自然科学版（英文版）

ISSN：1007-0214

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