Srimanta Santra

Physics-Informed Neural Network Surrogates with Polynomial Chaos-Based Uncertainty Propagation for Stochastic Model Predictive Control

An error decomposition is provided for the PINN-PCE surrogate that separates PCE truncation, stochastic quadrature, and PINN approximation errors and it is shown how the surrogate approximation error can be incorporated into tightened probabilistic constraints.