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.

中文翻译：

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通过交叉熵方法提高双稳态能量收集装置的性能

这项工作涉及解决非凸优化问题以提高能量收集设备的性能，该问题涉及非线性目标函数和不连续约束。这个优化问题旨在寻找合适的参数配置，使双稳态能量收集系统回收的电能最大化，根据动态系统响应和从 0 到 1 的混沌测试获得的二元分类器制定。提出了一种结合惩罚和交叉熵方法的随机求解策略并进行了数值测试。进行计算实验以通过与参考解决方案进行比较来解决所提出的优化方法的性能，参考解决方案是通过在精细数值网格中进行详尽搜索而获得的。