Surrogate empowered Sim2Real transfer of deep reinforcement learning for ORC superheat control-Reference-Cited by-同舟云学术

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Surrogate empowered Sim2Real transfer of deep reinforcement learning for ORC superheat control

Published:2024-02 Issue: Volume:356 Page:122310
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Lin Runze,Luo Yangyang,Wu Xialai,Chen Junghui,Huang Biao,Su Hongye,Xie Lei

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference37 articles.

1. Recent developments of control strategies for organic Rankine cycle (ORC) systems;Zhang;Trans Inst Meas Control,2019

2. Model based control for waste heat recovery heat exchangers Rankine cycle based system in heavy duty trucks;Grelet,2015

3. Gain scheduling control of waste heat energy conversion systems based on an LPV (linear parameter varying) model;Zhang;Energy,2016

4. An optimal control design of organic ranking cycle under disturbances;Wu,2018

5. Integrated operation design and control of Organic Rankine Cycle systems with disturbances;Wu;Energy,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Developing Purely Data-Driven Multi-Mode Process Controllers Using Inverse Reinforcement Learning;Computer Aided Chemical Engineering;2024

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