Differentially coprime kernel representations and closed-loop identification of nonlinear systems

We utilize the differential kernel representation concept to convert a nonlinear closed-loop identification problem into one of open-loop identification utilizing a nonlinear version of the Youla parametrization. The main advantage of our approach using kernel representations over fractional descriptions is that we address a larger class of nonlinear systems