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N. Lawrence (Larry) Ricker Department of Chemical Engineering University of Washington Box 351750 (365 Benson Hall)Seattle, WA 98195-1750 Phone: 206-543-8786 Fax: 206-685-3451 or 206-543-3778 ricker@u.washington.edu |
INTERESTS:
As the chemical industry matures, companies are increasingly concerned with process efficiency, i.e., the best possible use of raw materials and energy resources, and waste reduction. Changes in process design are one way to improve efficiency. Other opportunities arise during process operation.
For the last decade my group has been developing control algorithms for use in complex continuous and batch processes. Applications have included biological, waste-treatment, and classical chemical processes. The key idea is to develop a mathematical model that incorporates the key process features, then use the model directly in a control strategy. Such methods have come to be known as Model Predictive Control (MPC).
MPC offers significant improvements over conventional control methods. For example, the figure below compares a nonlinear version of MPC to a classical single-loop (SISO) strategy proposed by other researchers. The application is the Tennessee Eastman Industrial Challenge Process. The objective is to hold three variables within the limits shown as dashed horizontal lines. The strategies are equally good for product composition (%G and %H in the figure), but the conventional strategy (dotted lines) violates the limits on production. Also, it does a much poorer job of controlling reactor pressure, which is a critical variable from the point of view of safety and operating costs.
An outgrowth of this work is the MPC Toolbox for MATLAB (Morari and Ricker, 1994), which is currently installed at over 1000 industrial and academic institutions world-wide.
Selected Recent Publications:
M. S. Gelormino and N. L. Ricker, "Model-Predictive Control of a Combined Sewer System," Int. J. Control 59(3), 793-816 (1994).
M. Morari and N. L. Ricker, Model Predictive Control Toolbox for use with Matlab (tutorials and reference manual), The MathWorks, Inc, Natick, MA, 1994.
N. L. Ricker and J. H. Lee, "Nonlinear Model Predictive Control of the Tennessee Eastman Challenge Process," Computers Chem. Engng. 19, 961-981(1995).
Wu, C.; Danielson, J. D. S.; Callis, J. B.; Eaton, M.; Ricker, N. L. "Remote, in-line monitoring of emulsion polymerization of styrene by short wavelength near-infrared spectroscopy Part I: performance during normal runs", Process Control and Quality, 8, 1-23(1996); Part II: Performance in the face of process upsets", Process Control and Quality, 8, 25-40(1996).
Pearsall, T. P.; Brown, N.; Ricker, N. L.; Johnson, M. "Flux monitoring and control in epitaxy by chemical vapor deposition," J. Crystal Growth, Vol. 188, 63-68(1998).