Abstract
Recently proposed algorithms for multivariable system identification by subspace techniques involve the computation of the so-called “oblique projection” to estimate the system order and system matrices. The paper shows that this computation can be performed without actually solving any least-square problems, and that orthogonal transformations only should be applied to the original input-output data sequences. Both deterministic and combined deterministic-stochastic identification problems can be dealt with.
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