Subspace Methods
Mostrando 1-12 de 16 artigos, teses e dissertações.
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1. Modal Parameter Extraction of a Huge Four Stage Centrifugal Compressor Using Operational Modal Analysis Method
Abstract In recent years, modal analysis has become one of the essential methods for modification and optimization of dynamic characteristics of engineering structures. This is the first published study to identify modal parameters of a complex four-stage centrifugal compressor using Operational Modal Analysis (OMA). Vibrational response was measured contin
Lat. Am. j. solids struct.. Publicado em: 03/05/2018
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2. Updating Finite Element Model Using Stochastic Subspace Identification Method and Bees Optimization Algorithm
Abstract This study investigates the application of operational modal analysis along with bees optimization algorithm for updating the finite element model of structures. Bees algorithm applies instinctive behavior of honeybees as they look for nectar of flowers. The parameters that needed to be updated are uncertain parameters such as geometry and material
Lat. Am. j. solids struct.. Publicado em: 26/04/2018
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3. Estudo de métodos de identificação multivariável baseados em subespaços aplicados ao monitoramento da integridade de estruturas / Study of subspace-based identification methods applied to structural health monitoring
Structural Health Monitoring (SHM) is a multidisciplinary research field, which covers techniques, technologies and methods which are essential to perform a continuous and intelligent diagnosis about mechanical structure integrity. The development of structures with improved durability, improved operational safety and reduced maintenance cost are the main re
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 29/07/2011
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4. A new block algorithm for full-rank solution of the Sylvester-observer equation
A new block algorithm for computing a full rank solution of the Sylvester-observer equation arising in state estimation is proposed. The major computational kernels of this algorithm are: 1) solutions of standard Sylvester equations, in each case of which one of the matrices is of much smaller order than that of the system matrix and (furthermore, this small
Publicado em: 2011
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5. Subspace predictive control. / Controle preditivo com enfoque em subespaços.
Model Predictive Control (MPC) technology is widely used in chemical process industries. Subspace identification (SID) on the other hand has proven to be an efficient alternative for classical system identification methods. Based on the results from MPC and SID, it was developed in the late 90s a new control approach, called Subspace Predictive Control (SPC)
Publicado em: 2009
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6. Metodos de subespaços para identificação de sistemas : propostas de alterações, implementações e avaliações / Subspace methods for systems identification : proposals of alterations, implementations and evaluations
This study presents the theoretical foundations of multivariable data modeling in state space by Subspace Methods for Systems Identification of linear time invariant, discrete time, systems. The work contains some basic concepts of dynamic systems, a little of history and the elements of systems identification, state space models and extended state space mod
Publicado em: 2008
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7. Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
A new iterative scheme that uses the residual vector as search direction is proposed and analyzed for solving large-scale nonsymmetric linear systems, whose matrix has a positive (or negative) definite symmetric part. It is closely related to Richardson's method, although the stepsize and some other new features are inspired by the success of recently propos
Computational & Applied Mathematics. Publicado em: 2008
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8. Applied nonlinear dynamics of non-smooth mechanical systems
This paper introduces practically important concept of local non-smoothness where any dynamical system can be considered as smooth in a finite size subspace of global hyperspaceomega. Global solution is generated by matching local solutions obtained by standard methods. If the dynamical system is linear in all subspaces then an implicit global analytical sol
Journal of the Brazilian Society of Mechanical Sciences and Engineering. Publicado em: 2006-12
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9. Identificação e controle estocasticos descentralizados de sistemas interconectados multivariaveis no espaço de estado
In this thesis a decentralized methodology for linear state space identification of discrete time, serially interconnected multivariable stochastic systems is proposed. The global system identificationis achieved by means of the individual identification of its subsystems through some state space methods for identification of multivariable systems and time s
Publicado em: 2005
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10. Modelagem computacional de dados e controle inteligente no espaço de estado / State space computational data modelling and intelligent control
This study presents contributions for state space multivariable computational data modelling with discrete time invariant as well as with time varying linear systems. A proposal for Deterministic-Estocastica Modelling of noisy data, MOESP_AOKI Algorithm, is made. We present proposals forsolving the Discrete-Time Algebraic Riccati Equation as well as the asso
Publicado em: 2005
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11. Dimensionality reduction using mean conditional entropy applied for bioinformatics and image processing problems / "Redução de dimensionalidade utilizando entropia condicional média aplicada a problemas de bioinformática e de processamento de imagens"
Dimensionality reduction is a very important pattern recognition problem with many applications. Among the dimensionality reduction techniques, feature selection was the main focus of this research. In general, most dimensionality reduction methods that may be found in the literature privilegiate cases in which the data is linearly separable and with only tw
Publicado em: 2004
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12. Tecnicas de identificação modal multivariavel orientadas a subespaços
The analysis oí the dynamical behaviour oí structures is oí great economical and technological importance. The present work brings a contribution to this field, presenting time domam identification methods based on rea1ization theory. The methods are implemented for multivariable measurements through the use of the subspace approách. Numerical simulation
Publicado em: 2003