  We propose to solve a constrained distribution steering problem, i.e.,
steering a stochastic linear system from an initial distribution to some final,
desired distribution subject to chance constraints. We do so by characterizing
the cumulative distribution function in the chance constraints and by using the
absolute distance between two probability density functions using the
corresponding characteristic functions. We consider discrete-time, time-varying
linear systems with affine feedback. We demonstrate the proposed approach on a
2D double-integrator perturbed by various disturbances and initial conditions.
