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Model Predictive Control: An Overview and Selected Applications

Originally delivered Sep 30, 2009
Source: AIChE
  • Type:
    Archived Webinar
  • Level:
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Model Predictive Control (MPC) is the most commonly advanced control technique applied in the chemical process industries. In this Webinar, basic feedback control principles are reviewed using a simple surge tank example. Important challenges in petroleum refining and other large-scale chemical processes, which largely led to the development of MPC algorithms, are discussed. Next, the fundamental framework for MPC, based on optimization concepts, is developed, and low-order, constrained examples are used to illustrate the main points. Finally, selected MPC applications, including the development of a closed-loop artificial pancreas, are presented.


B Wayne Bequette

B. Wayne Bequette is a Professor of Chemical and Biological Engineering and Technical Manager for the Northern Regional Manufacturing Center of the Department of Energy Clean Energy Smart Manufacturing Innovation Institute (CESMII) at Rensselaer Polytechnic Institute, where his research efforts are focused on the modeling and control of biomedical and chemical process systems. He serves as Board Secretary for the American Automatic Control Council (AACC) and as President of the Computer Aids for Chemical Engineering (CACHE) Corporation. Dr. Bequette is a founding member of the Editorial...Read more

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Webinar content is available with the kind permission of the author(s) solely for the purpose of furthering AIChE’s mission to educate, inform and improve the practice of professional chemical engineering. All other uses are forbidden without the express consent of the author(s).