Pseudo-linear indentification: Optimal joint parameter and state estimation of linear stochastic MIMO systems

Show simple item record

dc.contributor.author Hopkins, Mark
dc.contributor.author VanLandingham, Hugh
dc.date.accessioned 2009-09-21T12:54:46Z
dc.date.available 2009-09-21T12:54:46Z
dc.date.issued 1988
dc.identifier.citation Proceedings of the American Control Conference, Atlanta, Georgia, 1988 en_US
dc.identifier.uri http://hdl.handle.net/1850/10567
dc.description.abstract This paper presents a new method of joint parameter and stale estimation called pseudo-linear identification (PLID), extending a method given by Salut et.al. (I) to the more gencr31 case where the system inputs and output measurements arc corrupted by noise. PLID can be applied to linear, strictly proper, completely observable, completely controllable, discrete-time MIMO systems with known structure and unknown parameters, without assumptions about pole and zero locations. It is proved, under standard gaussian assumptions, that for lime- invariant systems PLI D is the optimal estimator (in the mean-square error sense) of the states and parameters conditioned on the input and output measurements; and. under a reasonable criterion for persistency of excitation, that the PLID parameter estimates converge a.e. to the true parameter values. en_US
dc.language.iso en_US en_US
dc.title Pseudo-linear indentification: Optimal joint parameter and state estimation of linear stochastic MIMO systems en_US
dc.type Proceedings en_US

Files in this item

Files Size Format View
MHopkinsAricles2004.pdf 1.779Mb PDF View/Open

This item appears in the following Collection(s)

Show simple item record

Search RIT DML


Advanced Search

Browse