In control theory we often wish to find a feedback control $u$ to stabilize a given linear system $\dot{x} = A x + B u, y= Cx$. The problem of linear adaptive control consists in constructing such a controller, using measurements of $y$ only, without precise a priori knowledge about the matrices $A$, $B$, and $C$.
During the 1970s and 1980s several adaptive control algorithms appeared, under restrictive assumptions on the matrices. Notably the transfer function $c (sI - A)^{-1}b$, in the single-input, single-output case, was required to be minimum-phase (have stable zeroes). It was thought that some of those assumptions were indeed necessary.