12 citations · 13 across the 3 of their papers we have counts for
3 papers
physics.chem-ph2023
Introducing Hybrid Modeling with Time-series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization
Niranjan Sitapure, Joseph S Kwon
Most existing digital twins rely on data-driven black-box models, predominantly using deep neural recurrent, and convolutional neural networks (DNNs, RNNs, and CNNs) to capture the…
cond-mat.mtrl-sci2023★ 1 cited
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers
Niranjan Sitapure, Joseph S. Kwon
For prediction and real-time control tasks, machine-learning (ML)-based digital twins are frequently employed. However, while these models are typically accurate, they are custom-d…
eess.SY2020★ 12 cited
Data-driven feedback stabilization of nonlinear systems: Koopman-based model predictive control
Abhinav Narasingam, Joseph Sang-Il Kwon
In this work, a predictive control framework is presented for feedback stabilization of nonlinear systems. To achieve this, we integrate Koopman operator theory with Lyapunov-based…