Dynamic market conditions and the evolving integration of chemical production with other industries (e.g., energy generation) call for a closer coordination between production management (planning, scheduling) and process control decisions in the operation of a chemical process. The integration of business decisions with dynamic information from the control layer is a difficult task owing to the range of time scales involved in making the respective decisions, and the corresponding need to balance long-term prediction with real-time execution. In this presentation, we focus on the “mesoscale” of the process decision-making hierarchy, and report on our recent developments that allow for a closer coordination between production scheduling and supervisory control systems. We introduce a new time scale-bridging framework, based on capturing the input-output behavior of the chemical process in a low-dimensional model, which is then used in scheduling calculations. We extend these concepts to the integration of scheduling and model predictive control, as the most widely-used advanced control strategy in industry. Furthermore, we introduce an approach for exploiting historical process data in building the aforementioned scale-bridging models. We demonstrate our results on several examples, including an industry-based case study concerning the demand-response operation of an air separation plant and an application to managing energy use in buildings.
Michael Baldea is Assistant Professor and Frank A. Liddell, Jr. Centennial Fellow in the McKetta Department of Chemical Engineering and a core faculty member in the Institute for Computational Engineering and Sciences (ICES) at The University of Texas at Austin. He received his Diploma (2000) and M.Sc. degree (2001) in Chemical Engineering from "Babes-Bolyai" University in Cluj-Napoca, Romania and obtained a Ph.D. in Chemical Engineering from the University of Minnesota in 2006. Prior to joining The University of Texas, he held industrial research positions with Praxair Technology Center in Tonawanda, NY and GE Global Research in Niskayuna, NY. He has received several research and service awards, including the NSF CAREER award, the Moncrief Grand Challenges Award, the ACS Doctoral New Investigator award, the Model-Based Innovation Prize from Process Systems Enterprise and the Best Referee Award from the Journal of Process Control. His research interests include the dynamics, optimization and control of process and energy systems, areas in which he has co-authored one book, three book chapters and over 90 peer-reviewed journal and conference articles.