Nearly Optimal State Feedback Controls for Stochastic Systems with Wideband Noise Disturbances
Much of optimal stochastic control theory is concerned with diffusion models. Such models are often only idealizations (or limits in an appropriate sense) of the actual physical process, which might be driven by a wide bandwidth (not white) process or be a discrete parameter system with correlated driving noises. Optimal or nearly optimal controls, derived for the diffusion models, would not normally be useful or even of much interest, if they were not also ‘nearly optimal’ for the physical system which the diffusion approximates. Under quite broad conditions, the ‘nearly optimal’ control for the physical process do have this robustness property, even when compared to controls which can depend on all the (past) driving noise. We treat the problem over a finite time interval, as well as the average cost per unit time problem. Weak convergence methods provide the appropriate analytical tools.
KeywordsInvariant Measure Weak Convergence Stochastic System Wiener Process Average Cost
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