WebCAST seminar on "Dynamic Real-Time Optimization: Concepts in Modeling, Algorithms and Properties" by Lorenz T. Biegler Bayer Professor of Chemical Engineering at Carnegie Mellon University Date: November 28, 2007, 10 am-12 pm (EST) Dial-in from the comfort of your office to hear the presentation Deadline to Register: November 23, 2007 (details at http://www.castdiv.org/WebCAST.htm) Abstract: The webcast develops and discusses nonlinear programming (NLP) strategies for the optimization of nonlinear dynamic models that arise in both off-line and on-line applications in chemical process engineering. In particular, Dynamic Real-Time Optimization can play a significant part in the decision-making hierarchy that includes logistics, planning, scheduling and control. Its basic components deal with estimation of the system and identification of a system model, optimization of a system model and regulation to reject disturbances. Moreover, the inclusion of a consistent set of nonlinear process models is essential in order to coordinate optimization decisions made at different levels in the hierarchy. The webcast briefly presents and summarizes nonlinear programming methods for dynamic optimization. In particular, it discusses simultaneous NLP formulations along with large-scale NLP solvers for dynamic optimization and demonstrates its effectiveness with real-world examples. Also described is the extension of this approach to nonlinear model predictive control (NMPC). In the last few years, these have emerged as efficient and reliable on-line NMPC strategies. Finally, the webcast discusses the integration of dynamic models for off-line optimization to on-line model predictive control (MPC). In particular, we will discuss a fast sensitivity-based nonlinear MPC strategy that is not only consistent with rigorous off-line dynamic optimization models but requires very little on-line computation. A similar strategy will also be presented for moving horizon estimation with nonlinear models. All of these concepts will be illustrated with several case studies drawn from process engineering. Biographical Sketch: Professor Larry Biegler is the Bayer Professor of Chemical Engineering at Carnegie Mellon University. He received a BS degree from Illinois Institute of Technology and MS and PhD degrees from University of Wisconsin, Madison, all in chemical engineering. Prof. Biegler's research projects are in the areas of design research and systems analysis. His research centers on the development and application of concepts in optimization theory, operations research, and numerical methods for process design, analysis, and control. He has received numerous honors and awards including the Presidential Young Investigator Award from the National Science Foundation, the Curtis McGraw Research Award from the American Society for Engineering Education, and the Computing in Chemical Engineering Award from the CAST Division of the American Institute of Chemical Engineers.