On Identification of Parallel Cascade Serial Systems
2011 (English)In: IFAC Proceedings Volumes (IFAC-PapersOnline), IFAC , 2011Conference paper (Refereed)
We consider identification of systems with a parallel serial (cascade) structure with multiple-input and multiple-output signals. The statistical properties of estimated models are studied with respect to input signals and possible sensor locations. The quality of the estimates are analyzed by means of the asymptotic covariance matrix of the estimated parameters. This is an extension of previous work on identification of cascaded linear systems. The key result concerns systems where the sub-systems have common dynamics. An interesting observation is that for this case the variance for the parameters belonging to the unmeasured subsystem always is larger than for the other sub-systems. This is not true for general parameters. The variance results can be used for optimal input and sensor location design. The results are illustrated by some simple FIR examples and numerical evaluations.
Place, publisher, year, edition, pages
IFAC , 2011.
Grey box modelling; Input and excitation design
IdentifiersURN: urn:nbn:se:kth:diva-55894DOI: 10.3182/20110828-6-IT-1002.02068ScopusID: 2-s2.0-84866762254OAI: oai:DiVA.org:kth-55894DiVA: diva2:472032
Proceedings of the 18th IFAC World Congress, 2011, Milano, Italy
FunderSwedish Research Council
QC 201201232012-01-232012-01-032013-09-05Bibliographically approved