  This work deals with the solution of a non-convex optimization problem to
enhance the performance of an energy harvesting device, which involves a
nonlinear objective function and a discontinuous constraint. This optimization
problem, which seeks to find a suitable configuration of parameters that
maximize the electrical power recovered by a bistable energy harvesting system,
is formulated in terms of the dynamical system response and a binary classifier
obtained from 0 to 1 test for chaos. A stochastic solution strategy that
combines penalization and the cross-entropy method is proposed and numerically
tested. Computational experiments are conducted to address the performance of
the proposed optimization approach by comparison with a reference solution,
obtained via an exhaustive search in a refined numerical mesh. The obtained
results illustrate the effectiveness and robustness of the cross-entropy
optimization strategy (even in the presence of noise or in moderately higher
dimensions), showing that the proposed framework may be a very useful and
powerful tool to solve optimization problems involving nonlinear energy
harvesting dynamical systems.
