Passivity preserving model reduction via spectral factorization

We present a novel model-order reduction (MOR) method for linear time-invariant systems that preserves passivity and is thus suited structure-preserving MOR port-Hamiltonian (pH) systems. Our algorithm exploits the well-known spectral factorization of Popov function by solution Kalman–Yakubovich–Popov (KYP) inequality. It performs directly on factor inheriting original system’s sparsity enabling in large-scale context. analysis reveals corresponding to minimal an associated algebraic Riccati equation preferable from model perspective benefits pH-preserving methods such as modified version iterative rational Krylov (IRKA). Numerical examples demonstrate our approach can produce high-fidelity reduced-order models close (unstructured) H2-optimal models.