  Supervisor localization can be applied to distribute a monolithic supervisor
into local supervisors. Performing supervisor localization can be
computationally costly. In this work, we consider systems that evolve over
time. We study how to reuse the results from a previous supervisor
localization, to more efficiently compute local supervisors when the system is
adapted. We call this approach transformational supervisor localization, and
present algorithms for the procedure. The efficiency of the procedure is
experimentally evaluated.
