Model reduction for linear systems and linear time-delay systems from input/output data

An algorithm for the estimation of the moments of linear systems and linear time-delay systems from input/output data is proposed. The estimate, which converges to the moments of the system, is exploited to construct a family of reduced order models. These models asymptotically match the moments of the unknown system to be reduced. The computational complexity of the algorithm is analyzed and the use of the algorithm is illustrated by a benchmark example.