Linear system approximation via covariance equivalent realizations
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A truncation technique for model reduction to simultaneously match a specified number of output covariance derivatives is described. These COVariance Equivalent Realizations which match q + 1 covariance derivatives are called "q-COVERs." In general q-COVERs are not unique. The additional freedom is used herein so that the q-COVER obtained also matches q Markov parameters. The truncation technique uses a form of the observability matrices of the full-order system to determine a priori the order required of the reduced order model to match a specified number of output covariance derivatives and Markov parameters. The resulting realization is shown to be independent of the basis of the complete model to within a unitary transformation. Stability conditions for the reduced order model are also described, and the relationships are established between stochastically equivalent realizations and the q-COVERs. 1985.