Direct data‐driven design of switching controllers

Abstract

Summary Switching linear models can be used to represent the behavior of hybrid, time‐varying, and nonlinear systems, while generally providing a satisfactory trade‐off between accuracy and complexity. Although several control design techniques are available for such models, the effect of modeling errors on the closed‐loop performance has not been formally evaluated yet. In this paper, a data‐driven synthesis scheme is thus introduced to design optimal switching controllers directly from data, without needing a model of the plant. In particular, the theory will be developed for piecewise affine controllers, which have proven to be effective in many real‐world engineering applications. The performance of the proposed approach is illustrated on some benchmark simulation case studies.