Feedback control theory & Model order reduction for stochastic equations

We analyze structure-preserving model order reduction methods for Ornstein-Uhlenbeck processes and linear SPDEs with multiplicative noise based on balanced truncation with non-zero initial data. We then marry these model order reduction methods with stochastic optimal control theory and prove error bounds for a class of linear quadratic regulator problems. We discuss the application of our approach to enhanced sampling methods from non-equilibrium statistical mechanics.

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