Tae Hoon Oh

According to our database, Tae Hoon Oh authored at least 8 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Bayesian optimization with search space movement for cooling crystallization process.

Tae Hoon Oh, Kazuki Kato, Osamu Tonomura, Ken-Ichiro Sotowa

Comput. Chem. Eng., 2025

2024

Quantitative comparison of reinforcement learning and data-driven model predictive control for chemical and biological processes.

Tae Hoon Oh

Comput. Chem. Eng., February, 2024

Model-based safe reinforcement learning for nonlinear systems under uncertainty with constraints tightening approach.

Yeonsoo Kim, Tae Hoon Oh

Comput. Chem. Eng., 2024

2022

Primal-dual differential dynamic programming: A model-based reinforcement learning for constrained dynamic optimization.

Jong Woo Kim, Tae Hoon Oh, Sang Hwan Son, Jong Min Lee

Comput. Chem. Eng., 2022

2021

Move blocked model predictive control with guaranteed stability and improved optimality using linear interpolation of base sequences.

Sang Hwan Son, Byung Jun Park, Tae Hoon Oh, Jong Woo Kim, Jong Min Lee

Int. J. Control, 2021

Model-based reinforcement learning and predictive control for two-stage optimal control of fed-batch bioreactor.

Jong Woo Kim, Byung Jun Park, Tae Hoon Oh, Jong Min Lee

Comput. Chem. Eng., 2021

2020

Model-plant mismatch learning offset-free model predictive control.

Sang Hwan Son, Jong Woo Kim, Tae Hoon Oh, Jong Min Lee

CoRR, 2020

Convergence analysis of the deep neural networks based globalized dual heuristic programming.

Jong Woo Kim, Tae Hoon Oh, Sang Hwan Son, Dong Hwi Jeong, Jong Min Lee

Autom., 2020