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arXiv · 2605.15851

Uncertainty Propagation under Residual Disturbances: A Smart-Home Case Study

Guanru Pan·Dirk Reinhardt·Sebastien Gros·Timm Faulwasser
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Abstract

This paper presents a data-driven framework for uncertainty propagation under unmeasured or statistically unmodeled (unstructured) disturbances. We consider residual disturbances, which consolidate all unstructured disturbances into a single quantity that can be estimated from data. Under mild assumptions, the resulting stochastic predictor is causal and distributionally consistent, enabling efficient uncertainty quantification through polynomial chaos expansions and higher-order Chebyshev inequalities. The proposed method is validated using experimental data from a smart home in Norway.

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Guanru Pan, Dirk Reinhardt, Sebastien Gros, Timm Faulwasser. 2026-05-15. Uncertainty Propagation under Residual Disturbances: A Smart-Home Case Study. https://arxiv.org/abs/2605.15851

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