Identification for control: Deterministic algorithms and error bounds

Abstract

This dissertation deals with frequency domain identification of linear dynamic systems in a deterministic set-up. Various untuned algorithms are suggested, including one which is robustly convergent and asymptotically optimal (in n-width sense) for a finite model order. The suggested algorithms can easily be implemented in commercially available software for convex optimization.