Abstract
Abstract There is experimental evidence that the N4SID method performs poorly in certain conditions where the past signals (past inputs and past outputs) and future input spaces are nearly parallel. This paper describes a subspace identification technique based on a preliminary orthogonal decomposition of the data spaces which is more robust and reliable than N4SID in critical cases. Numerical results are included demonstrating a substantial improvement of performance in some experimental conditions.
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