Feedback Solution to Optimal Switching Problems with Switching Cost

TL;DR

This paper addresses optimal switching among nonlinear systems with costs for switching, developing an approximate dynamic programming method that considers previous modes, and demonstrates its effectiveness through numerical examples.

Contribution

It introduces a novel approach incorporating switching costs into optimal control, with an approximate dynamic programming method that accounts for previous modes.

Findings

The method effectively approximates optimal switching policies.

Switching costs influence the optimal cost-to-go function.

Numerical examples validate the proposed approach.

Abstract

The problem of optimal switching between nonlinear autonomous subsystems is investigated in this study where the objective is not only bringing the states to close to the desired point, but also adjusting the switching pattern, in the sense of penalizing switching occurrences and assigning different preferences to utilization of different modes. The mode sequence is unspecified and a switching cost term is used in the cost function for penalizing each switching. It is shown that once a switching cost is incorporated, the optimal cost-to-go function depends on the already active subsystem, i.e., the subsystem which was engaged in the previous time step. Afterwards, an approximate dynamic programming based method is developed which provides an approximation of the optimal solution to the problem in a feedback form and for different initial conditions. Finally, the performance of the method is analyzed through numerical examples.