WORST-CASE INPUT-OUTPUT IDENTIFICATION

We consider worst-case l 1 identication of causal linear shift-invariant systems from time series. Many results are given on general aspects of identi-cation algorithm performance, existence of optimal algorithms, robust convergence , and input (experiment) design. The identication methodology studied here is compatible with the modelling requirements of modern robust control design. Notation R; R + the reals, and the nonnegative reals, respectively. Z + the set of positive integers. R n the set of all n-tuples of real numbers. l 1 the normed space of sequences x = fx k 2 Rg k0 with the norm kxk 1 = sup k0 jx k j < 1. l 1 the normed space of sequences x = fx k 2 Rg k0 with the norm kxk 1 = P k0 jx k j < 1. We shall use the notation l 1 also for bounded sequence spaces for which the integer-valued indexing set can be put into one-to-one correspondence with the set of natural numbers f0g [ Z + .

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