Least squares methods for H/sub infinity / control-oriented system identification

A series of system identification algorithms that yield identified models which are compatible with current robust controller design methodologies is presented. These algorithms are applicable to a broad class of stable, distributed, linear, shift-invariant plants. The a priori information necessary for their application consists of a lower bound on the relative stability of the unknown plant, an upper bound on a certain gain associated with the unknown plant, and an upper bound on the noise level. The a posteriori data information consists of a finite number of corrugated point frequency response estimates of the unknown plant. The extent to which certain standard Hilbert-space or least-squares method are applicable to the H/sub infinity / system identification problem considered is examined. Results are established that connect the H/sub 2/ error of the least-squares methods to the H/sub infinity / error needed for control-oriented system identification.<
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