Frequency Domain identification, Subspace Methods and Periodic Excitation
1995 (English)Report (Other academic)
Recent frequency domain identification algorithms based on subspace based techniques are discussed. The algorithms construct a state-space model by means of extraction of the signal subspace from a matrix constructed from frequency data. A singular value decomposition plays a key part in the subspace extraction. The subspace methods are non-iterative methods in contrast to classical iterative parametric optimization techniques. The use of periodic excitation leads to a leakage free discrete Fourier transform of the measured data as well as simple noise reduction possibilities by averaging.
Place, publisher, year, edition, pages
Linköping: Linköping University , 1995. , 5 p.
LiTH-ISY-R, ISSN 1400-3902 ; 1765
State-space models, Singular value decomposition, Non-iterative methods
IdentifiersURN: urn:nbn:se:liu:diva-55270ISRN: LITH-ISY-R-1765OAI: oai:DiVA.org:liu-55270DiVA: diva2:315865