  Motivated by the goal of learning controllers for complex systems whose
dynamics change over time, we consider the problem of designing control laws
for systems that switch among a finite set of unknown discrete-time linear
subsystems under unknown switching signals. To this end, we propose a method
that uses data to directly design a control mechanism without any explicit
identification step. Our approach is online, meaning that the data are
collected over time while the system is evolving in closed-loop, and are
directly used to iteratively update the controller. A major benefit of the
proposed online implementation is therefore the ability of the controller to
automatically adjust to changes in the operating mode of the system. We show
that the proposed control mechanism guarantees stability of the closed-loop
switched linear system provided that the switching is slow enough.
Effectiveness of the proposed design technique is illustrated for two aerospace
applications.
