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)

Focus

Modeling, optimization, and control of chemical processes.

Courses Taught

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

Awards & Honors

• 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)

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, A Survey of Industrial Model Predictive Control Technology, Control Engineering Practice, Volume 11, Issue 7, July 2003, Pages 733-764, 2003.
• Kenneth R. Muske, Thomas A Badgwell, Disturbance Modeling for Offset-free Linear Model Predictive Control, 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, Robust Stability Conditions for SISO Model Predictive Control Algorithms, 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.