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dc.contributor.advisorSawan, M. Edwin
dc.contributor.authorJiang, Chen
dc.date.accessioned2013-11-22T22:49:35Z
dc.date.available2013-11-22T22:49:35Z
dc.date.issued2013-05
dc.identifier.othert13021
dc.identifier.urihttp://hdl.handle.net/10057/6820
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
dc.description.abstractIn this thesis, a method of designing a Kalman filter for a linear, discrete-time, singularly perturbed stochastic system using the delta operator was introduced. This unified approach, which is based on the delta operator, was the main method used to unify the continuous-time system and the discrete-time system. This method has many advantages over the q-operator: it makes the system simpler, it has better finite word-length characteristics, and the truncation and round-off error is less. One of the singular perturbation techniques, quasi-steady state approximation, was used to separate the system into a slow subsystem and a fast subsystem. Then, the exact solution of the Kalman filter and the minimized mean square error for the full-order system, and the composite solution of the Kalman filter and minimized mean square error for the two subsystems were solved. This method was applied using a numerical example in which the steady-state Kalman filter solution was found.
dc.format.extentviii, 31p.
dc.language.isoen_US
dc.publisherWichita State University
dc.rightsCopyright Chen Jiang, 2013.
dc.subject.lcshElectronic dissertations
dc.titleKalman filter design for large-scale systems by using unified approach
dc.typeThesis


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