Algorithms for robust identification in H-infinity with nonuniformly spaced frequency response data

In this paper, first a two-stage robustly convergent identification algorithm in H-infinity for nonuniformly spaced data is proposed. The worst-case error of the algorithm converges to zero faster than polynomial rates in the noise-free case when the identified system is an exponentially stable discrete-time system. The algorithm is characterized by a rational interpolation step with fixed poles at zero and infinity. Next, a minimax algorithm with better convergence properties is introduced. Sensitivity of the algorithms to small variations in the frequency values is also studied.