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

Optimization and Control