Uncertainty quantification in hybrid dynamical systems

Uncertainty quantification (UQ) techniques are frequently used to ascertain output variability in systems with parametric uncertainty. Traditional algorithms for UQ are either system-agnostic and slow (such as Monte Carlo) or fast with stringent assumptions on smoothness (such as polynomial chaos an...

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Bibliographic Details
Main Authors: Sahai, T., Pasini, J. M.
Format: Conference Proceeding
Language:English
Subjects:
Chaos
Monte Carlo methods
Polynomials
Switches
Trajectory
Uncertainty
Vectors
Online Access:Request full text
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Summary:Uncertainty quantification (UQ) techniques are frequently used to ascertain output variability in systems with parametric uncertainty. Traditional algorithms for UQ are either system-agnostic and slow (such as Monte Carlo) or fast with stringent assumptions on smoothness (such as polynomial chaos and Quasi-Monte Carlo). In this work, we develop a fast UQ approach for hybrid dynamical systems by extending the polynomial chaos methodology to these systems. To capture discontinuities, we use a wavelet-based Wiener-Haar expansion. We develop a boundary layer approach to propagate uncertainty through separable reset conditions. The above methods are demonstrated on example problems.
ISSN:0191-2216
DOI:10.1109/CDC.2012.6426653