Worst-case input-output identification

Abstract

We consider worst-case l¹ identification of causal linear shift-invariant systems from time series. Many results are given on general aspects of identification algorithm performance, existence of optimal algorithms, robust convergence, and input (experiment) design. The identification methodology studied here is compatible with the modelling requirements of modern robust control design.