  A unified solution to adaptive approximation-based control for nonlinear
systems with accurate and inaccurate state measurement is synthesized in this
study. Starting from the standard adaptive approximation-based controller with
accurate state measurement, its corresponding physical interpretation,
stability conclusion, and learning ability are rigorously addressed when facing
additive measurement inaccuracy, and explicit answers are obtained in the
framework of both controller matching and system matching. Finally, it proves
that, with a certain condition, the standard adaptive approximation-based
controller works as a unified solution for the cases with accurate and
inaccurate measurement, and the solution can be extended to the nonlinear
system control problems with extra unknown dynamics or faults in actuator
and/or process dynamics. A single-link robot arm example is used for the
simulation demonstration of the unified solution.

Systems and Control;Systems and Control