DocumentCode
358242
Title
Minmax filtering in Volterra systems
Author
Basin, Michael V. ; Guzman, Irma R Valadez
Author_Institution
Dept. of Phys. & Math. Sci., Autonomous Univ. of Nuevo Leon, Mexico
Volume
2
fYear
2000
fDate
2000
Firstpage
1380
Abstract
Examines the minmax filtering problem for linear integral Volterra systems with deterministic uncertainties over observations given by either a differential equation or an integral Volterra equation as well. The solution is based on the Pontryagin minimum (maximum) principle, the Lagrange multipliers method, and the duality principle in Volterra systems. First, the optimal control (regulator) problem is solved and the Riccati equation for the optimal gain matrix is obtained for integral Volterra systems, and, second, the minmax filtering equation for the optimal estimate of a Volterra system state and the Riccati equation for its ellipsoid matrix are obtained over both differential and integral observations. Thus, in the case of deterministic uncertainties, it is possible to form a closed system of the minmax filtering equations for an integral system state over integral observations, using only two filtering variables, the optimal estimate and its ellipsoid matrix, although the analogous result cannot be reached in stochastic systems
Keywords
Riccati equations; duality (mathematics); filtering theory; integral equations; linear systems; matrix algebra; maximum principle; minimum principle; Lagrange multipliers method; Pontryagin maximum principle; Pontryagin minimum principle; deterministic uncertainties; differential observations; duality principle; ellipsoid matrix; integral Volterra equation; integral observations; linear integral Volterra systems; minmax filtering; optimal gain matrix; Differential equations; Ellipsoids; Filtering; Integral equations; Lagrangian functions; Minimax techniques; Nonlinear filters; Riccati equations; State estimation; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2000. Proceedings of the 2000
Conference_Location
Chicago, IL
ISSN
0743-1619
Print_ISBN
0-7803-5519-9
Type
conf
DOI
10.1109/ACC.2000.876727
Filename
876727
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