nagy2.pdf (1.46 MB)
Download file

Distributional uncertainty analysis using polynomial chaos expansions

Download (1.46 MB)
conference contribution
posted on 2011-01-13, 16:14 authored by Zoltan NagyZoltan Nagy, Richard D. Braatz
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.



  • Aeronautical, Automotive, Chemical and Materials Engineering


  • Chemical Engineering


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.




VoR (Version of Record)

Publication date



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.