Random spherical uncertainty in estimation and robustness

A theorem is formulated that gives an exact probability distribution for a linear function of a random vector uniformly distributed over a ball in n-dimensional space. This mathematical result is illustrated via applications to a number of important problems of estimation and robustness under spheri...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 45; no. 11; pp. 2145 - 2150
Main Authors Polyak, B.T., Shcherbakov, P.S.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.11.2000
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Automatic control
Computational complexity
Control theory
Dynamical systems
Mathematical analysis
Parameter estimation
Polynomials
Probability distribution
Robust stability
Robustness
Stability
State estimation
Uncertainty
Vectors
Vectors (mathematics)
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Summary:A theorem is formulated that gives an exact probability distribution for a linear function of a random vector uniformly distributed over a ball in n-dimensional space. This mathematical result is illustrated via applications to a number of important problems of estimation and robustness under spherical uncertainty. These include parameter estimation, characterization of attainability sets of dynamical systems, and robust stability of affine polynomial families.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0018-9286
1558-2523
DOI:10.1109/9.887645