Convergent algorithms for frequency weighted L-2 model reduction

This paper is concerned with computing an L-2-optimal reduced-order model for a given stable multivariable linear system in the presence of input and output frequency weightings. By parametrizing a class of reduced-order models in terms of an orthogonal projection and using manifold techniques as tools, both continuous and iterative algorithms are derived and their convergence properties are established. As an application, we show that an L-2 optimal reduced-order filter in the closed-loop sense can be computed using these algorithms. (C) 1997 Elsevier Science B.V.