Show simple item record

dc.contributor.authorLekutai, Gaviphaten_US
dc.date.accessioned2014-03-14T21:37:59Z
dc.date.available2014-03-14T21:37:59Z
dc.date.issued1993-05-05en_US
dc.identifier.otheretd-06112009-063610en_US
dc.identifier.urihttp://hdl.handle.net/10919/43172
dc.description.abstract

A computationally efficient estimation technique is presented for a class of nonlinear systems consisting of memoryless nonlinearities combined with linear dynamic processes. The modeling approach is based on a useful sampled-data method for simulating such systems by adding a system state for each nonlinear element. The nonlinear estimator is next developed along the lines of the Kalman filter, but in contrast to the Extended Kalman Filter (EKF) the present approach does not require the linearization step after each recursive cycle. In addition, it also appears free from the well known divergence problems associated with the EKF. It is demonstrated that this new method is directly applicable to those feedback systems with both major nonlinearities, for example saturating gain blocks, and stochastic disturbances-- an example extremely difficult to handle with EKF techniques.

en_US
dc.format.mediumBTDen_US
dc.publisherVirginia Techen_US
dc.relation.haspartLD5655.V855_1993.L458.pdfen_US
dc.subjectElectrodynamicsen_US
dc.subject.lccLD5655.V855 1993.L458en_US
dc.titleKalman filtering in noisy nonlinear systems using a jump matrix approachen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineElectrical Engineeringen_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06112009-063610/en_US
dc.date.sdate2009-06-11en_US
dc.date.rdate2009-06-11
dc.date.adate2009-06-11en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record