Model-set adaptation in variable-structure MM estimation by hypothesis testing

X. Rong Li

doi:10.1109/ACC.1998.703072

Model-set adaptation in variable-structure MM estimation by hypothesis testing

X. Rong Li

University of New Orleans

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The key component in variable-structure multiple-model (VSMM) estimation is model-set adaptation (MSA). This paper formulates MSA as hypothesis testing problems and provides effective solutions, which have some desirable optimality properties. The hypotheses to be tested are in general composite, N-ary, multivariate, and worst of all, not necessarily disjoint. The results form a theoretical foundation and guideline for developing good and practical MSA algorithms.

Original language	English
Title of host publication	Proceedings of the 1998 American Control Conference, ACC 1998
Pages	2439-2443
Number of pages	5
DOIs	https://doi.org/10.1109/ACC.1998.703072
State	Published - 1998
Externally published	Yes
Event	1998 American Control Conference, ACC 1998 - Philadelphia, PA, United States Duration: 24 Jun 1998 → 26 Jun 1998

Publication series

Name	Proceedings of the American Control Conference
Volume	4
ISSN (Print)	0743-1619

Conference

Conference	1998 American Control Conference, ACC 1998
Country/Territory	United States
City	Philadelphia, PA
Period	24/06/98 → 26/06/98

Access to Document

10.1109/ACC.1998.703072

Cite this

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title = "Model-set adaptation in variable-structure MM estimation by hypothesis testing",

abstract = "The key component in variable-structure multiple-model (VSMM) estimation is model-set adaptation (MSA). This paper formulates MSA as hypothesis testing problems and provides effective solutions, which have some desirable optimality properties. The hypotheses to be tested are in general composite, N-ary, multivariate, and worst of all, not necessarily disjoint. The results form a theoretical foundation and guideline for developing good and practical MSA algorithms.",

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AB - The key component in variable-structure multiple-model (VSMM) estimation is model-set adaptation (MSA). This paper formulates MSA as hypothesis testing problems and provides effective solutions, which have some desirable optimality properties. The hypotheses to be tested are in general composite, N-ary, multivariate, and worst of all, not necessarily disjoint. The results form a theoretical foundation and guideline for developing good and practical MSA algorithms.

UR - https://www.scopus.com/pages/publications/84881346402

U2 - 10.1109/ACC.1998.703072

DO - 10.1109/ACC.1998.703072

M3 - 会议稿件

AN - SCOPUS:84881346402

SN - 0780345304

SN - 9780780345300

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BT - Proceedings of the 1998 American Control Conference, ACC 1998

T2 - 1998 American Control Conference, ACC 1998

Y2 - 24 June 1998 through 26 June 1998

ER -

Model-set adaptation in variable-structure MM estimation by hypothesis testing

Abstract

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Conference

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