%0 Journal Article %1 markolf2022recedinghorizon %A Markolf, Lukas %A Stursberg, Olaf %D 2022 %J SN Computer Science %K control isac-www %N 62 %T Receding-Horizon Control of Constrained Switched Systems with Neural Networks as Parametric Function Approximators %U https://link.springer.com/article/10.1007/s42979-022-01442-0#author-information %V 4 %X This work studies receding-horizon control of discrete-time switched linear systems subject to polytopic constraints for the continuous states and inputs. The objective is to approximate the optimal receding-horizon control strategy for cases in which the online computation is intractable due to the necessity of solving mixed-integer quadratic programs in each discrete time instant. The proposed approach builds upon an approximated optimal finite-horizon control law in closed-loop form with guaranteed constraint satisfaction. The paper derives the properties of recursive feasibility and asymptotic stability for the proposed approach. A numerical example is provided for illustration and evaluation of the approach.