In this contribution, we report our progress concerning a practicable, projective method for output nonlinear moment matching. First, we explain the time-domain interpretation of output Krylov subspace-based moment matching for linear systems. Then, based on [Ionescu and Astolfi 2016], the steady-state perception of output moments and moment matching for nonlinear systems is given. Finally, some simplifications to approximate the solution of the arising partial differential equation (PDE) are proposed towards a practical, numerical algorithm for nonlinear model order reduction.     «

In this contribution, we report our progress concerning a practicable, projective method for output nonlinear moment matching. First, we explain the time-domain interpretation of output Krylov subspace-based moment matching for linear systems. Then, based on [Ionescu and Astolfi 2016], the steady-state perception of output moments and moment matching for nonlinear systems is given. Finally, some simplifications to approximate the solution of the arising partial differential equation (PDE) are pr...     »