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This paper studies the partially observed stochastic optimal control problemfor systems with state dynamics governed by partial differential equations(PDEs) that leads to an extremely large problem. First, an open-loopdeterministic trajectory optimization problem is solved using a black-boxsimulation model of the dynamical system. Next, a Linear Quadratic Gaussian(LQG) controller is designed for the nominal trajectory-dependent linearizedsystem which is identified using input-output experimental data consisting ofthe impulse responses of the optimized nominal system. A computationalnonlinear heat example is used to illustrate the performance of the proposedapproach.

A Separation-based Approach to Data-based Control for Large-Scale Partially Observed Systems