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Estimation and identification using ...

Chen, Chii-Chuan.

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Estimation and identification using a real-time MME algorithm.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Estimation and identification using a real-time MME algorithm./
Author:	Chen, Chii-Chuan.
Description:	158 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 4001.
Contained By:	Dissertation Abstracts International64-08B.
Subject:	Engineering, Mechanical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3102350

Estimation and identification using a real-time MME algorithm.
Chen, Chii-Chuan.

Estimation and identification using a real-time MME algorithm. - 158 p.

Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 4001.

Thesis (Ph.D.)--State University of New York at Buffalo, 2003.

A real-time or pseudo real-time (RTMME) estimation technique is presented in current research, based on the Minimum Model Error estimation algorithm. Given a set of measurements and with the nominal sensor variance information, the RTMME then can be performed by "windowing", "swapping", and "push-back" to find an optimal weighting for further use. The time needed for estimating the states are small enough that the RTMME could be used as a "real-time" estimator.Subjects--Topical Terms:

783786
Engineering, Mechanical.

Estimation and identification using a real-time MME algorithm.
LDR:01902nmm 2200301 4500 001 1866546
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035 $a (UnM)AAI3102350
035 $a AAI3102350
040 $a UnM $c UnM
100 1 $a Chen, Chii-Chuan. $3 1953926
245 1 0 $a Estimation and identification using a real-time MME algorithm.
300 $a 158 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 4001.
500 $a Major Professor: Daniel Joseph Mook.
502 $a Thesis (Ph.D.)--State University of New York at Buffalo, 2003.
520 $a A real-time or pseudo real-time (RTMME) estimation technique is presented in current research, based on the Minimum Model Error estimation algorithm. Given a set of measurements and with the nominal sensor variance information, the RTMME then can be performed by "windowing", "swapping", and "push-back" to find an optimal weighting for further use. The time needed for estimating the states are small enough that the RTMME could be used as a "real-time" estimator.
520 $a Next, system identification based on the RTMME is shown. This system identification may also be employed in pseudo real-time. A correlation technique is employed to select the best candidate function; followed by the linear and nonlinear least squares methods for the estimation of the model parameters/coefficients.
520 $a Finally, an important application for RTMME is demonstrated. The RTMME is shown to serve as a sensor failure and/or system malfunction detection tool. These uses are demonstrated by examples.
590 $a School code: 0656.
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Engineering, System Science. $3 1018128
650 4 $a Engineering, Aerospace. $3 1018395
690 $a 0548
690 $a 0790
690 $a 0538
710 2 0 $a State University of New York at Buffalo. $3 1017814
773 0 $t Dissertation Abstracts International $g 64-08B.
790 1 0 $a Mook, Daniel Joseph, $e advisor
790 $a 0656
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3102350