Thomas Badgwell

Professor of Practice

Educational Qualifications

Ph.D., Chemical Engineering, The University of Texas at Austin (1992)
M.S., Chemical Engineering, The University of Texas at Austin (1990)
B.S., Chemical Engineering, Rice University (1982)

Courses Taught

CHE 348 Numerical Methods in Chemical Engineering and Problem Solving
CHE 354 Transport Processes
CHE 360 Process Dynamics and Control

Focus

Modeling, optimization, and control of chemical processes.

Awards & Honors

Babatunde A. Ogunnaike Control Practice Award, American Automatic Control Council (AACC), 2024
Distinguished Industrial Lecturer, Institute of Electrical and Electronics Engineers (IEEE) Control Systems Society, 2024
Control Global Process Automation Hall of Fame, 2022
Computing Practice Award, Computing and Systems Technology (CAST) Division, 2013
Fellow of the American Institute of Chemical Engineers (AIChE), 2011

Selected Publications

Badgwell T.A., Qin S.J., Model Predictive Control in Practice, In: Baillieul J., Samad T. (eds), Encyclopedia of Systems and Control. Springer, London, 2019.
Joohyun Shin, Thomas A.Badgwell, Kuang-Hung Liu, Jay H. Lee, Reinforcement Learning – Overview of Recent Progress and Implications for Process Control, Computers & Chemical Engineering, Volume 127, 4 August 2019, Pages 282-294, 2019.
Joe Qin, Thomas A. Badgwell, Control Engineering Practice, Volume 11, Issue 7, July 2003, Pages 733-764, 2003.
Kenneth R. Muske, Thomas A Badgwell, Journal of Process Control, Volume 12, Issue 5, August 2002, Pages 617-632, 2002.
Allgöwer F., Badgwell T.A., Qin J.S., Rawlings J.B., Wright S.J., Nonlinear Predictive Control and Moving Horizon Estimation—An Introductory Overview, In: Frank P.M. (eds) Advances in Control. Springer, London, 1999.
Thomas A. Badgwell, Automatica, Volume 33, Issue 7, Pages 1357-1361, 1997.
Thomas A. Badgwell, Robust Model Predictive Control of Stable Linear Systems, International Journal of Control, 68:4, 797-818, 1997.

☰