Sparse Switching Times Optimization and a Sweeping Hessian Proximal Method

摘要

The switching times optimization problem for switched dynamical systems, with fixed initial state, is considered. A nonnegative cost term for changing dynamics is introduced to induce a sparse switching structure, that is, to reduce the number of switches. To deal with such problems, an inexact Newton-type arc search proximal method, based on a parametric local quadratic model of the cost function, is proposed. Numerical investigations and comparisons on a small-scale benchmark problem are presented and discussed.