Dynamic Extension for Adaptive Backstepping Control of Uncertain Pure-Feedback Systems

An adaptive backstepping algorithm is developed for a class of uncertain systems in pure-feedback form. The control based on dynamic state feedback that allows to compensate parametric uncertainties which enter linearly into the system. As possible nominal case, extension just order one required, addition dynamics identifiers adaptation. regularity law only requires standard assumptions.