  The aim of this paper and associated presentation is to put forward
derivative-free optimization methods for control design. The important element,
still ignored at the end of 2011 in systems and control (i.e. this element has
apparently never been used so far in the systems and control litterature), is
that derivative-free optimization methods were relatively recently proven to
converge not only on smooth objective functions but also on most non-smooth and
discontinuous objective functions. This opens an avenue of posibilities for
solving problems unyielding to classical optimization techniques.
  Original abstract:
  This paper investigates the performance of using a direct search method to
design optimal Static Output Feedback (SOF) controllers for Linear Time
Invariant (LTI) systems. Considering the old age of both SOF problems and
direct search methods, surprisingly good performances will be obtained compared
to a state-of-the-art method. The motivation is to emphasize the fact that
direct search methods are too much neglected by the control community. These
methods are very rich for practical purposes on a lot of complex problems
unyielding to classical optimization techniques, like linear matrix
inequalities, thanks to their ability to explore even non-smooth functions on
non-convex feasible sets.
  Again, the key element here are the relatively new strong theoretical
convergence guarantees of derivatie-free methods. Thanks to these, using such
optimization methods is superior to other methods without convergence
guarantees (like most iterative LMI schemes).
