17 citations · 25 across the 9 of their papers we have counts for
4 papers · 1 filter
Reinforcement Learning-Driven Plant-Wide Refinery Planning Using Model Decomposition
Zhouchang Li, Runze Lin, Hongye Su +1
In the era of smart manufacturing and Industry 4.0, the refining industry is evolving towards large-scale integration and flexible production systems. In response to these new dema…
Dynamic fault detection and diagnosis for alkaline water electrolyzer with variational Bayesian Sparse principal component analysis
Qi Zhang, Weihua Xu, Lei Xie +1
Electrolytic hydrogen production serves as not only a vital source of green hydrogen but also a key strategy for addressing renewable energy consumption challenges. For the safe pr…
Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Overview and Perspectives
Runze Lin, Junghui Chen, Lei Xie +1
In the context of Industry 4.0 and smart manufacturing, the field of process industry optimization and control is also undergoing a digital transformation. With the rise of Deep Re…
Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control
Runze Lin, Yangyang Luo, Xialai Wu +4
The Organic Rankine Cycle (ORC) is widely used in industrial waste heat recovery due to its simple structure and easy maintenance. However, in the context of smart manufacturing in…