Visible to the public Design of Networked Control Systems for Chemical Processes


The chemical industry is a vital sector of the US economy. Optimal operation and management of abnormal situations are major challenges in the process industries since, for example, abnormal situations account for at least $10 billion in annual lost revenue in the US alone. This realization has motivated significant research in the area of process control to ensure safe and efficient process operation. Traditionally, process control systems utilize dedicated, wired links to measurement sensors and control actuators to regulate appropriate process variables at desired values. While this paradigm to process control has been successful, we are currently witnessing an augmentation of the existing, dedicated local control networks with additional networked (wired or wireless) actuator/sensor devices which have become cheap and easy-to-install the last few years. Such an augmentation in sensor information and networked-based availability of data has the potential to transform the ability of the control systems to optimize plant performance and deal with abnormal situations (fault-tolerance). However, there is currently a lack of methods for the analysis and design of networked process control systems. The central objective of this research program is to develop a general and practical framework for the analysis and design of networked process control systems. In terms of the main accomplishments in the context of the first three years of this program, systematic methods were proposed for: (a) the design of networked control architecture for nonlinear chemical processes, b) the design of networked distributed Lyapunov-based model predictive control systems for nonlinear systems subject to sensor/actuator/network data losses, and c) monitoring and control system reconfiguration for networked and distributed control systems. We also carried out successful applications of the developed methods to chemical processes and renewable energy generation systems using realistic process models.

This research has already resulted in two books, 16 refereed journal papers, 14 refereed conference proceedings papers and numerous invited and contributed presentations. Funds were used to partially support seven doctoral students Jinfeng Liu (ChE), Wei Qi (ChE), Xiazhong Chen (ChE), David Chilin (ChE), Mohsen Heidarinejad (EE), Matt Ellis (ChE) and Liangfeng Lao (ChE). Jinfeng Liu defended his doctoral dissertation in June 2011 and he joined as Assistant Professor the Department of Chemical Engineering and Materials Science at the University of Alberta. Xiazhong Chen and Mohsen Heidarinejad recently defended their doctoral theses and will join Exxon Mobil and Western Digital, respectively, as Senior Control Engineers. Furthermore, one hispanic minority doctoral student, David Chilin, recently defended his doctoral thesis and works as Energy Policy Consultant. Wei Qi completed his Masters Thesis in Summer 2011 and moved on to UC Berkeley. Matt Ellis and Liangfeng Lao are second year doctoral students. Three undergraduate students worked on research projects related to the goals of this program. In addition, the work carried out in the context of this grant led to fundamental concepts and methods and allowed the PIs to attract additional funding from the Abnormal Situation Management Consortium to support the above students.

Award ID: 0930746

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Design of Networked Control Systems for Chemical Processes