Subspace Identification as Multi-Step Predictions Optimization

P. Trnka and V. Havlena (Czech Republic)


Subspace Identification, Geometrical Projections, Multistep Predictor, Regression Methods.


We will show that apparently complicated and not easy to understand expressions with geometrical projections ap pearing in the algorithms of subspace identification for lin ear state space models, can be quite simply derived from optimizing these models for multi-step predictions on mea sured data samples using least squares. Furthermore we will show the advantages which brings the use of multi step predictions instead of single-step predictions arising from regression methods.

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