A5070891335- Advanced Control Systems Optimization
- Fault Detection and Control Systems
- Control Systems and Identification
- Process Optimization and Integration
- Carbon Dioxide Capture Technologies
- Algal biology and biofuel production
- Iterative Learning Control Systems
- Biofuel production and bioconversion
- Microbial Metabolic Engineering and Bioproduction
- Membrane Separation and Gas Transport
- Catalysts for Methane Reforming
- Hybrid Renewable Energy Systems
- Adaptive Dynamic Programming Control
- Reinforcement Learning in Robotics
- Scheduling and Optimization Algorithms
- Phase Equilibria and Thermodynamics
- Advanced Battery Technologies Research
- Electric Vehicles and Infrastructure
- Catalytic Processes in Materials Science
- CO2 Reduction Techniques and Catalysts
- Mineral Processing and Grinding
- Chemical Looping and Thermochemical Processes
- Biodiesel Production and Applications
- Optical Network Technologies
- Advanced Statistical Process Monitoring
University of Southern California
2023-2025
Southern California University for Professional Studies
2023-2025
Korea Advanced Institute of Science and Technology
2015-2024
Material Sciences (United States)
2023-2024
University of Southern Somalia
2024
Korea University Medical Center
2023
University of Florida
2022
Government of the Republic of Korea
2020-2021
Northwest Evaluation Association
2021
Daejeon University
2020
The enzymatic hydrolysis of cellulose encounters various limitations that are both substrate- and enzyme-related. Although the crystallinity pure cellulosic Avicel plays a major role in determining rate by cellulases from Trichoderma reesei, we show it stays constant during conversion. mode action was investigated studying their kinetics on samples. A convenient method for reaching intermediate degrees with therefore developed initial cellulase-catalyzed demonstrated to be linearly...
Process monitoring is considered to be one of the most important problems in process systems engineering, which can benefited significantly from deep learning techniques. In this paper, neural networks are applied problem fault detection and classification illustrate their capability. First, formulated as network based problems. Then, trained perform detection, effects two hyperparameters (number hidden layers number neurons last layer) data augmentation on performance examined. Fault also...
This paper reviews methodological approaches for determining the carbon footprint of captured CO<sub>2</sub> as feedstock, and shows why some lead to suboptimal choices sources that increased consistency in life cycle assessment (LCA) studies on CCU is needed.
Abstract A general formulation of the moving horizon estimator is presented. An algorithm with a fixed‐size estimation window and constraints on states, disturbances, measurement noise developed, probabilistic interpretation given. The requires only one more tuning parameter (horizon size) than many well‐known approximate nonlinear filters such as extended Kalman filter (EFK), iterated EKF, Gaussian second‐order filter, statistically linearized filter. choice size allows user to achieve...
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTExtended Kalman Filter Based Nonlinear Model Predictive ControlJay H. Lee and N. Lawrence RickerCite this: Ind. Eng. Chem. Res. 1994, 33, 6, 1530–1541Publication Date (Print):June 1, 1994Publication History Published online1 May 2002Published inissue 1 June 1994https://pubs.acs.org/doi/10.1021/ie00030a013https://doi.org/10.1021/ie00030a013research-articleACS PublicationsRequest reuse permissionsArticle Views3852Altmetric-Citations257LEARN ABOUT...
Abstract A novel model predictive control technique geared specifically toward batch process applications is demonstrated in an experimental reactor system for temperature tracking control. The technique, called Batch‐MPC (BMPC), based on a time‐varying linear (representing nonlinear along fixed trajectory) and utilizes not only the incoming measurements from ongoing batch, but also information stored past batches. This particular feature shown to be essential achieving effective performance...