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Identification for distributed parameter systems

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Kubrusly, Carlos Silva (1976) Identification for distributed parameter systems. PhD thesis, University of Warwick.

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Official URL: http://webcat.warwick.ac.uk/record=b1748035~S15

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Abstract

This thesis considers the parameter identification problem for systems governed by partial differential equations. The various identification methods sire grouped into three disjoint classes namely: "Direct Methods", "Reduction to a Lumped Parameter System", and "Reduction to an Algebraic Equation".
The major subject investigated here is concerned with the applicability of stochastic approximation algorithms for identifying distributed parameter systems (DPS) operating in a stochastic environ­ment, where no restriction on probability distributions is imposed.
These algorithms are used as a straightforward identification procedure, converge to the real value of the parameters with probability one, and are suitable for on-line applications. In this way, a new identification method is developed for DPS described by linear models, driven by random inputs, and observed through noisy measurements. The very real case of noisy observations taken at a limited number of discrete points located in the spatial domain is considered. The proposed identifica­tion method assumes that a previous system classification has been performed, such that the model to be identified is known up to a set of space-varying parameters, where extraneous terms may be included.

Item Type: Thesis (PhD)
Subjects: Q Science > QA Mathematics
T Technology > TJ Mechanical engineering and machinery
Library of Congress Subject Headings (LCSH): System identification, Differential equations, Partial, Estimation theory, Distributed parameter systems
Official Date: 1976
Dates:
DateEvent
1976Submitted
Institution: University of Warwick
Theses Department: Department of Engineering
Thesis Type: PhD
Publication Status: Unpublished
Supervisor(s)/Advisor: Curtain, Ruth F.
Sponsors: Conselho Nacional de Pesquisas (Brazil)
Extent: vi, 186 leaves
Language: eng

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