  This paper proposes a multiple-model adaptive control methodology, using
set-valued observers (MMAC-SVO) for the identification subsystem, that is able
to provide robust stability and performance guarantees for the closed-loop,
when the plant, which can be open-loop stable or unstable, has significant
parametric uncertainty. We illustrate, with an example, how set-valued
observers (SVOs) can be used to select regions of uncertainty for the
parameters of the plant. We also discuss some of the most problematic
computational shortcomings and numerical issues that arise from the use of this
kind of robust estimation methods. The behavior of the proposed control
algorithm is demonstrated in simulation.
