An ɛ-embedding model-order reduction approach for differential-algebraic equation systems

In this article, we present a model-order reduction (MOR) approach for a large-scale linear differential-algebraic equation (DAE) system. This MOR approach is accomplished in two steps: First, by applying an e{open}-embedding method, we approximate a DAE system with an ordinary differential equation (ODE) system which has an artificial parameter e{open}. Next, we use the Krylov subspace and balanced truncation methods to reduce the resulting ODE system. Some important properties for linear systems, such as stability and passivity, have been analysed. The effectiveness of our approach is also successfully illustrated through numerical examples.