High order dynamic neuro observer: Application for ozone generator

Abstract

In this study the adaptive observing problem for nonlinear uncertain systems is analyzed. The considered nonlinear systems verify the so-called regular form. A new high-order sliding mode neural-observer is suggested to solve the aforementioned problem by means of the super-twisting algorithm. This observer is supplied with a new learning procedure which adaptive structure ensuring the practical stability for estimation scheme. The suggested approach was successfully applied for the state estimation of the corone discharge ozone generator. ©2008 IEEE.