It is well known that the performance of the (industry standard) field-orie
nted control (FOC) for induction motors is highly sensitive to uncertaintie
s in the rotor resistance. In this paper we describe how to use supervisory
control to obtain an adaptive implementation of FOC for current-fed machin
es. The unknown rotor resistance is assumed to belong to a discrete set, wh
ile the uncertain load torque ranges in a given compact set. Even though no
restrictions are a priori imposed on the size of these sets, their definit
ions reflect the prior knowledge of the designer, which is effectively inco
rporated in the supervisory control algorithm. The supervisor selects from
these sets values for the parameters to be applied to the FOG, a choice tha
t is made by continuously comparing suitably defined performance signals. W
e prove that the proposed supervisor achieves global stabilization of the s
ystem when the load torque is known to belong to a given finite set of valu
es, Apparently, this is the first globally convergent adaptive algorithm fo
r current-fed machines which simply adds adaptation to the widely popular F
OC and is not a radically new complicated controller, hence it is more like
ly to be adopted by practitioners. Some simulation results illustrate the p
roperties of the algorithm. Copyright (C) 2001 John Wiley & Sons, Ltd.