A norandom variational approach to stochastic linear quadratic Gaussian optimization involving fractional noises (FLQG)

It is shown that the problem of minimizing (maximizing) a quadratic cost functional (quadratic gain functional) given the dynamicsdx=(fx+gu)dt+hdb(t,a) whereb(t, a) is a fractional Brownian motion of ordera, 0<2a<1, can be solved completely (and meaningfully!) by using the dynamical equations of the moments ofx(t). The key is to use fractional Taylor's series to obtain a relation between differential and differential of fractional order.