We have investigated the performance of an adaptive optics
system subjected to changing atmospheric conditions, under the
guidance of the ALOPEX stochastic optimization.
Atmospheric distortions are smoothed out by means
of a deformable mirror, the shape of which can be altered
in order to follow the
rapidly changing atmospheric phase fluctuations.
In a simulation model,
the total intensity of the light measured on a central
area of the image (masking area)
is used as the cost function for our stochastic
optimization algorithm, while
the surface of the deformable mirror is approximated by a Zernike
polynomial expansion. Atmospheric turbulence is simulated by a number
of Kolmogorov filters.
The method's effectiveness, that is
its ability to follow the motion of the
turbulent wavefronts,
is studied in detail and as it pertains to
the size of the mirror's masking area,
to the number of Zernike polynomials used
and to the degree of the algorithm's
stochasticity in relation to the mean rate of change of atmospheric
distortions.
Computer simulations and a series of numerical experiments
are reported to show the successful implementation of the method.
