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Title: Distributional uncertainty analysis using polynomial chaos expansions
Authors: Nagy, Zoltan K.
Braatz, Richard D.
Issue Date: 2010
Publisher: © IEEE
Citation: NAGY, Z.K. and BRAATZ, R.D., 2010. Distributional uncertainty analysis using polynomial chaos expansions. IN: IEEE International Symposium on Computer-Aided Control System Design (CACSD), Yokohama, 8-10 Sept, 7pp.
Abstract: Abstract—A computationally efficient approach is presented that quantifies the influence of parameter uncertainties on the states and outputs of finite-time control trajectories for nonlinear systems, based on the approximate representation of the model via polynomial chaos expansion. The approach is suitable for studying the uncertainty propagation in open-loop or closed-loop systems. A quantitative and qualitative assessment of the method is performed in comparison to the Monte Carlo simulation technique that uses the nonlinear model for uncertainty propagation. The polynomial chaos expansion-based approach is characterized by a significantly lower computational burden compared to Monte Carlo approaches, while providing a good approximation of the shape of the uncertainty distribution of the process outputs. The techniques are applied to the crystallization of an inorganic chemical with uncertainties in the nucleation and growth parameters.
Description: This is a conference paper [©IEEE]. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/CACSD.2010.5612662
URI: https://dspace.lboro.ac.uk/2134/7734
Publisher Link: http://dx.doi.org/10.1109/CACSD.2010.5612662
ISBN: 9781424453542
Appears in Collections:Conference Papers and Presentations (Chemical Engineering)

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