Model reduction via balanced realizations: an extension and frequency weighting techniques

Two model-reduction methods for discrete systems related to balanced realizations are described. The first is a technique which utilizes the least controllable and observable subsystem in deriving a balanced discrete reduced-order model. For this technique as L/sup infinity / norm bound on the reduction error is given. The second method is a frequency-weighting technique for discrete- and continuous-time systems where the input-normal or output-normal realizations are modified to include a simple frequency weighting. For this technique, L/sup infinity / norm bounds on the weighted reduction errors are obtained.<
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