The stochastic estimation of parameters and states in linear and nonlinear time-delayed vibratory systems with distributed delay is explored. The approach consists of first employing a continuous time approximation to approximate the delayed integro-differential system with a large set of ordinary differential equations having stochastic excitations. Then the problem of state and parameter estimation in the resulting stochastic ordinary differential system is represented as an optimal filtering problem using a state augmentation technique. By adapting the extended Kalman-Bucy filter to the augmented filtering problem, the unknown parameters of the time-delayed system are estimated from noise-corrupted, possibly incomplete measurements of the states. Similarly, the upper bound of the distributed delay can also be estimated by the proposed technique. As an illustrative example to a practical problem in vibrations, the parameter, delay upper bound, and state estimation from noise-corrupted measurements in a distributed force model widely used for modeling machine tool vibrations in the turning operation is investigated. (C) 2013 Elsevier Ltd. All rights reserved.
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Tel Aviv Univ, Sch Elect Engn, IL-69978 Tel Aviv, Israel
Holon Inst Technol, Dept Elect Engn Med Elect, Holon, IsraelTel Aviv Univ, Sch Elect Engn, IL-69978 Tel Aviv, Israel
Gershon, E.
Allerhand, L. I.
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Holon Inst Technol, Dept Elect Engn Med Elect, Holon, IsraelTel Aviv Univ, Sch Elect Engn, IL-69978 Tel Aviv, Israel
Allerhand, L. I.
Shaked, U.
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Tel Aviv Univ, Sch Elect Engn, IL-69978 Tel Aviv, IsraelTel Aviv Univ, Sch Elect Engn, IL-69978 Tel Aviv, Israel
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Department of Mechanical and Aerospace Engineering, New Mexico State University, Las CrucesDepartment of Mechanical and Aerospace Engineering, New Mexico State University, Las Cruces
Torkamani S.
Butcher E.A.
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Department of Mechanical and Aerospace Engineering, New Mexico State University, Las CrucesDepartment of Mechanical and Aerospace Engineering, New Mexico State University, Las Cruces
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Curtin Univ, Dept Math & Stat, Perth, WA 6845, AustraliaCurtin Univ, Dept Math & Stat, Perth, WA 6845, Australia
Lin, Qun
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Loxton, Ryan
Xu, Chao
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Zhejiang Univ, Inst Cyber Syst & Control, Appl Dynam & Control, Hangzhou 310003, Zhejiang, Peoples R ChinaCurtin Univ, Dept Math & Stat, Perth, WA 6845, Australia
Xu, Chao
Teo, Kok Lay
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Curtin Univ, Dept Math & Stat, Perth, WA 6845, Australia
Zhejiang Univ, Inst Cyber Syst & Control, Hangzhou 310003, Zhejiang, Peoples R ChinaCurtin Univ, Dept Math & Stat, Perth, WA 6845, Australia