  This paper investigates the problem of data-driven stabilization for linear
discrete-time switched systems with unknown switching dynamics. In the absence
of noise, a data-based state feedback stabilizing controller can be obtained by
solving a semi-definite program (SDP) on-the-fly, which automatically adapts to
the changes of switching dynamics. However, when noise is present, the
persistency of excitation condition based on the closed-loop data may be
undermined, rendering the SDP infeasible. To address this issue, an auxiliary
function-based switching control law is proposed, which only requires
intermittent SDP solutions when its feasibility is guaranteed. By analyzing the
relationship between the controller and the system switching times, it is shown
that the proposed controller guarantees input-to-state practical stability
(ISpS) of the closed-loop switched linear system, provided that the noise is
bounded and the dynamics switches slowly enough. Two numerical examples are
presented to verify the effectiveness of the proposed controller.
