Georgia Tech Center for Process System Engineering

Jay H. Lee
ChBE Faculty Profile

Dr. Lee is currently Director of the Integrated Sensing, System Identification, and Control Laboratory (ISSICL) . His group is working on ways to use powerful computers, numerical optimization methods, information processing techniques, and novel sensors to improve the safety and efficiency of chemical and biological processes. The cornerstone of their research is a computer-based optimal control technique called Model Predictive Control (MPC), which has already seen applications on many industrial processes (>3000 worldwide applications) with some impressive results. The main components of MPC are the model, the sensors, and the optimal control algorithm. His research group focuses on integration - rather than mere enhancement of the individual components of MPC. They are developing modeling and system identification tools that allow the user to tailor the modeling efforts to specific end-goals of the control. They are developing techniques for integrating several different types of sensors and a process model so that accurate predictions can be made about the whole system including the behavior of those variables that cannot be measured as frequently or reliably as desired. They are also developing smart control algorithms that make optimal decisions while fully accounting for uncertainties in the model and sensed information. They are conducting a number of fundamental studies on data-assisted modeling, sensing, and control, which are designed to improve the integration step. In addition to the fundamental studies, they are conducting in parallel several application studies involving challenging industrial process control problems, including those that arise in particulate processes, mammalian cell reactors, polymer reactors, simulated moving bed separation systems, and pulp and paper processes.

Dr. Lee received the National Science Foundation's Young Investigator Award and a number of other research and teaching awards. He is also a co-author of the forthcoming book “Model Predictive Control.” He is a member of AIChE, IEEE, and ASEE, and participated in organizing several international conferences.

Current Projects

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Software


				Center for Process Systems Engineering School of Chemical & Biomolecular Engineering Georgia Institute of Technology 311 Ferst Drive, N.W. • Atlanta, GA 30332-0100 Phone: 404-385-2148 • Fax: 404-894-2866 E-mail: jay.lee@chbe.gatech.edu



				Jay H. Lee ChBE Faculty Profile Dr. Lee is currently Director of the Integrated Sensing, System Identification, and Control Laboratory (ISSICL) . His group is working on ways to use powerful computers, numerical optimization methods, information processing techniques, and novel sensors to improve the safety and efficiency of chemical and biological processes. The cornerstone of their research is a computer-based optimal control technique called Model Predictive Control (MPC), which has already seen applications on many industrial processes (>3000 worldwide applications) with some impressive results. The main components of MPC are the model, the sensors, and the optimal control algorithm. His research group focuses on integration - rather than mere enhancement of the individual components of MPC. They are developing modeling and system identification tools that allow the user to tailor the modeling efforts to specific end-goals of the control. They are developing techniques for integrating several different types of sensors and a process model so that accurate predictions can be made about the whole system including the behavior of those variables that cannot be measured as frequently or reliably as desired. They are also developing smart control algorithms that make optimal decisions while fully accounting for uncertainties in the model and sensed information. They are conducting a number of fundamental studies on data-assisted modeling, sensing, and control, which are designed to improve the integration step. In addition to the fundamental studies, they are conducting in parallel several application studies involving challenging industrial process control problems, including those that arise in particulate processes, mammalian cell reactors, polymer reactors, simulated moving bed separation systems, and pulp and paper processes. Dr. Lee received the National Science Foundation's Young Investigator Award and a number of other research and teaching awards. He is also a co-author of the forthcoming book “Model Predictive Control.” He is a member of AIChE, IEEE, and ASEE, and participated in organizing several international conferences. Current Projects Current Students Publications Reports Patents Software