  In this short note, the recently popular modifier-adaptation framework for
real-time optimization is discussed in tandem with the well-developed
trust-region framework of numerical optimization, and it is shown that the
basic version of the former is a simplification of the latter when the problem
is unconstrained. This relation is then exploited to propose a globally
convergent modifier-adaptation algorithm using already developed trust-region
theory. Cases when the two may not be equivalent and extensions to constrained
problems are also discussed.
