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Probabilistic model validation for uncertain nonlinear systems
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DOI：10.1016/j.automatica.2014.05.026.png)
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Abstract
En 中文
This paper presents a probabilistic model validation methodology for nonlinear systems in time-domain. The proposed formulation is simple, intuitive, and accounts both deterministic and stochastic nonlinear systems with parametric and nonparametric uncertainties. Instead of hard invalidation methods available in the literature, a relaxed notion of validation in probability is introduced. To guarantee provably correct inference, algorithm for constructing probabilistically robust validation certificate is given along with computational complexities. Several examples are worked out to illustrate its use. (C) 2014 Elsevier Ltd. All rights reserved.
Keywords:
Model validation
Uncertainty propagation
Optimal transport
Wasserstein distance
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