Control and Advanced
Simulation Engineering
Laboratory
(CASE Lab)
Control and Advansed Simulation Engineering Laboratory (CASE Lab)
Control and Advanced Simulation Engineering (CASE Lab) focuses on advanced modeling, simulation, and control strategies for complex chemical and energy systems. The laboratory integrates model-based approaches, artificial intelligence, and optimization techniques to improve process efficiency, sustainability, and robustness.
Our research addresses industrial-scale chemical processes, energy transition technologies, carbon-neutral production systems, and smart process operation under uncertainty. The lab emphasizes both theoretical development and practical industrial applications.
Research Themes / Interests
- Advanced Process Control (MPC, Robust Control, Economic MPC)
- Process Modeling and Dynamic Simulation
- Artificial Intelligence in Chemical Engineering
- Digital Twin and Smart Manufacturing
- Energy Systems Engineering and Green Hydrogen
- Carbon Neutral Chemical Production
- Biomass Conversion and Bioprocess Systems
- Process Optimization and Sustainability Analysis
Selected Publications
- Kongjui, W., Patthaveekongka, W., Jeraputra, C., Bumroongsri, P. (2025). Design of modular electrolysis and modular high-efficiency fuel cell systems for green hydrogen production and power generation with low emission of carbon dioxide. Computers & Chemical Engineering, 198, 109101.
- Bumroongsri, P. (2024). Value-added product from sugarcane molasses: Conversion of sugarcane molasses to non-caloric sweetener for applications in food and pharmaceutical industries. Bioresource Technology, 395, 130370.
- Lao-atiman, W., Bumroongsri, P., Arpornwichanop, A., Olaru, S., and Kheawhom, S. (2023). A novel state-of-health notion and its use for battery aging monitoring of zinc-air batteries. Computers and Chemical Engineering, 180, 108465.
- Yadbantung, R., Bumroongsri, P. (2022). Periodically time-varying economic model predictive control with applications to nonlinear continuous stirred tank reactors. Computers and Chemical Engineering, 157, 107602.
- Yadbantung, R., Bumroongsri, P. (2019). Tube-based robust output feedback MPC for constrained LTV systems with applications in chemical processes. European Journal of Control, 47, 11–19.
- Kusolsongtawee, T., Bumroongsri, P. (2018). Two-stage modeling strategy for industrial fluidized bed reactors in gas-phase ethylene polymerization processes. Chemical Engineering Research and Design, 140, 68–81.
Membership
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