Dissertations / Theses on the topic 'Subspace identification methods'
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Shi, Ruijie. "Subspace identification methods for process dynamic modeling /." *McMaster only, 2001.
Zhao, Yong. "Identification of ankle joint stiffness using subspace methods." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86800.
L'étude de la rigidité articulaire en réponse à une charge est un problème difficile car les couples réflexes et intrinsèques ne peuvent pas être mesurés séparément expérimentalement. En outre, la rigidité articulaire opère en boucle fermée car le couple de la cheville est réinjectée à travers la charge pour modifier la position de la cheville. Dans cette thèse, un modèle d'espace d'état pour la rigidité articulaire de la cheville est développé. Une méthode sous-espace à temps discret est ensuite utilisée pour estimer ce modèle d'espace d'état pour la rigidité globale. En considérant les variables instrumentales appropriées, la méthode sous-espace permet d'estimer le modèle espace d'état pour la rigidité articulaire en boucles ouverte et fermée. Cette thèse présente également une méthode sous-espace pour identifier les modèles d'espace d'état pour les systèmes biomédicauxou les systèmes variant dans le temps caractérisés par des phénomènes transitoires de courte durée. Les simulations et les résultats expérimentaux démontrent que ces algorithmes fournissent des estimations précises en fonction de leurs conditions propres.
Chui, Nelson Loong Chik. "Subspace methods and informative experiments for system identification." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298794.
Dahlen, Anders. "Identification of stochastic systems : Subspace methods and covariance extension." Doctoral thesis, KTH, Mathematics, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3178.
Zhou, Ning. "Subspace methods of system identification applied to power systems." Laramie, Wyo. : University of Wyoming, 2005. http://proquest.umi.com/pqdweb?did=1095432761&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.
Dahlén, Anders. "Identification of stochastic systems : subspace methods and covariance extension /." Stockholm : Tekniska högsk, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3178.
Lam, Xuan-Binh. "Uncertainty quantification for stochastic subspace indentification methods." Rennes 1, 2011. http://www.theses.fr/2011REN1S133.
En analyse modale operationelle, les paramètres modaux (fréquence, amortissement, déforméees) peuvent être obtenus par des méthodes d'identification de type sous espaces et sont définis à une incertitude stochastique près. Pour évaluer la qualité des résultats obtenus, il est essentiel de connaître les bornes de confiance sur ces résultats. Dans cette thèse sont développés des algorithmes qui calcule automatiquement de telles bornes de confiance pour des paramètres modaux caractèristiques d'une structure mécanique. Ces algorithmes sont validés sur des exemples industriels significatifs. L'incertitude est tout d'abord calculé sur les données puis propagée sur les matrices du système par calcul de sensibilité, puis finalement sur les paramètres modaux. Les algorithmes existants sur lesquels se basent cette thèse dérivent l'incertitude des matrices du système de l'incertitude sur les covariances des entrées mesurées. Dans cette thèse, plusieurs résultats ont été obtenus. Tout d'abord, l'incertitude sur les déformées modales est obtenue par un schema de calcul plus réaliste que précédemment, utilisant une normalisation par l'angle de phase de la composante de valeur maximale. Ensuite, plusieurs méthodes de sous espaces et non seulement les méthodes à base de covariance sont considérées, telles que la méthode de réalisation stochastique ERA ainsi que la méthode UPC, à base des données. Pour ces méthodes, le calcul d'incertitude est explicité. Deu autres problèmatiques sont adressés : tout d'abord l'estimation multi ordre par méthode de sous espace et l'estimation à partir de jeux de données mesurées séparément. Pour ces deux problèmes, les schemas d'incertitude sont développés. En conclusion, cette thèse s'est attaché à développer des schemas de calcul d'incertitude pour une famille de méthodes sous espaces ainsi que pour un certain nombre de problèmes pratiques. La thèse finit avec le calcul d'incertitudes pour les méthodes récursives. Les méthodes sous espaces sont considérées comme une approche d'estimation robuste et consistante pour l'extraction des paramètres modaux à partir de données temporelles. Le calcul des incertitudes pour ces méthodes est maintenant possible, rendant ces méthodes encore plus crédible dans le cadre de l'exploitation de l'analyse modale
Nilsen, Geir Werner. "Topics in open and closed loop subspace system identification : finite data-based methods." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, 2005. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1752.
Ivanova, Elena. "Identification de systèmes multivariables par modèle non entier en utilisant la méthode des sous-espaces." Thesis, Bordeaux, 2017. http://www.theses.fr/2017BORD0561/document.
The identification of systems by fractional models was initiated in the 1990s and various results have been obtained since. Nevertheless, most of these results are based on prediction error methods (PEM) of identification, based on the minimization of the norm of the estimation error. Apparent in 1996, the subspace methods are relatively new in the theory of the identification of linear systems. Based on geometric projections and linear algebra, they present an alternative to classical methods based on linear or nonlinear regression. They allow estimating the matrices of the state-space representation of a system. In the context of fractional systems, a pseudo-state-space representation generalizes the notion of state-space representation by introducing an additional parameter which is the commensurable order.Currently, the subspace method for non-integer systems has only been applied inthe time domain. It is then developed in this thesis for such a class of systems in the frequency domain. Moreover, since non-integer systems are continuous time systems, datapre-filtering is necessary to respect the causality of the signals and to be able to realize the identification. A study of the different filtering methods in the context of subspaceidentification is then carried out in order to deduce their advantages and disadvantages in the time domain. Finally, the method has been applied to a thermal diffusion system.The obtained models are generalized for several input heat flows, considering their temperature available at several measurement points
Jorajuria, Corentin. "Estimation de l'amortissement des aubages en analyse modale opérationnelle." Electronic Thesis or Diss., Ecully, Ecole centrale de Lyon, 2024. http://www.theses.fr/2024ECDL0003.
European goals to reduce air traffic environmental impacts leads to design new civilian turbojet engines. These new designs can result in more severe aeroelastic risks for turbojet engines. In this regard, understanding and predicting dissipation phenomena is a key industrial challenge. As these phenomena can be very wide and complex, experimental approaches take an important role to understand damping. This thesis focuses on the estimation of damping of fan of civilian turbojet engines. To this end, estimation methods in frequency and time domain have been studied. The estimation issues are addressed thanks to a test rig making possible to measure vibratory responses of rotating full-scale fan in vacuum conditions using piezoelectric excitations. Moreover, subspace identification methods, showing particular advantages for the estimation of modes of rotating fans, have been investigated more specifically. Estimation performances of these techniques have been assessed over numerical models. Then, these techniques have been applied over vibratory measurements of a rotating fan in vacuum conditions. Furthermore, experimental data of fans in operation show that excitations can induce significant transient responses. Accordingly, an experimental study evaluating the effect of unsteady responses over modal characterization has been carried out. This experimental study has been performed thanks to modal tests using excitations with different unsteady rate. Finally, estimation methods showing encouraging results over modal tests of a rotating fan in vacuum conditions have been applied over experimental data obtained in operational conditions
Srinivas, L. "FIR System Identification Using Higher Order Cumulants -A Generalized Approach." Thesis, Indian Institute of Science, 1994. https://etd.iisc.ac.in/handle/2005/637.
Srinivas, L. "FIR System Identification Using Higher Order Cumulants -A Generalized Approach." Thesis, Indian Institute of Science, 1994. http://hdl.handle.net/2005/637.
Bonis, Ioannis. "Optimisation and control methodologies for large-scale and multi-scale systems." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/optimisation-and-control-methodologies-for-largescale-and-multiscale-systems(6c4a4f13-ebae-4d9d-95b7-cca754968d47).html.
Gautier, Guillaume. "Diagnostic vibratoire des systèmes mécaniques par subspace fitting." Thesis, Tours, 2015. http://www.theses.fr/2015TOUR4026/document.
In this thesis, a subspace fitting (SF) method is presented for the identification of mechanical parameters and assessment of the health condition of vibrating structures. The SF method attempts to extract, from subspace identification methods (4SID), a system observability matrix of the system and correlate them with a theoretical observability matrix. The originality of this work is to obtain the theoretical observability matrix from a finite element model (EF) of the structure. By adjusting unknown parameters of the FE model, the mechanical properties of the vibrating structure are identified. Computational costs of such a procedure are reduced by considering a model reduction method based on the excitations and sensors location. The method is evaluated for the identification of natural frequencies of a vibrating structure. Numerical and experimental applications are assessed to show the relevance of such an approach. In particular, it is highlighted that the SF method can accurately identify the natural frequencies of a structure to high noise levels
Zhao, Wancheng. "A Structural Damage Identification Method Based on Unified Matrix Polynomial Approach and Subspace Analysis." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1206652627.
Kim, Yoonhwak. "The Effects of Assumption on Subspace Identification using Simulation and Experiment Data." Master's thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5666.
M.S.
Masters
Civil, Environmental, and Construction Engineering
Engineering and Computer Science
Civil Engineering; Structures and Geotechnical Engineering
GANDINO, EDOARDO. "Diagnostics of machines and structures: dynamic identification and damage detection." Doctoral thesis, Politecnico di Torino, 2013. http://hdl.handle.net/11583/2506356.
Jenča, Pavol. "Identifikace parametrů elektrických motorů metodou podprostorů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219678.
Mestrah, Ali. "Identification de modèles sous forme de représentation d'état pour les systèmes à sortie binaire." Electronic Thesis or Diss., Normandie, 2023. http://www.theses.fr/2023NORMC255.
This thesis focuses on parametric modeling of invariant linear systems from binary output measurements. This identification problem is addressed via the use ofsubspace methods. These methods allow the estimation of state-space models, an added benefit of these methods being the fact that their implementation doesnot require the prior knowledge of the order of the system. These methods are initially adapted to high resolution data processing, the objective of this thesis istherefore their adaptation to the identification using binary measurements. In this thesis we propose three subspace methods. Convergence properties of two ofthem are established. Monte Carlo simulation results are presented to show the good performance, but also limits, of these methods
PIOLDI, Fabio. "Time and Frequency Domain output-only system identification from earthquake-induced structural response signals." Doctoral thesis, Università degli studi di Bergamo, 2017. http://hdl.handle.net/10446/77137.
Lassami, Nacerredine. "Représentations parcimonieuses et analyse multidimensionnelle : méthodes aveugles et adaptatives." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2019. http://www.theses.fr/2019IMTA0139.
During the last decade, the mathematical and statistical study of sparse signal representations and their applications in audio, image, video processing and source separation has been intensively active. However, exploiting sparsity in multidimensional processing contexts such as digital communications remains a largely open problem. At the same time, the blind methods seem to be the answer to a lot of problems recently encountered by the signal processing and the communications communities such as the spectral efficiency. Furthermore, in a context of mobility and non-stationarity, it is important to be able to implement adaptive processing solutions of low algorithmic complexity to ensure reduced consumption of devices. The objective of this thesis is to address these challenges of multidimensional processing by proposing blind solutions of low computational cost by using the sparsity a priori. Our work revolves around three main axes: sparse principal subspace tracking, adaptive sparse source separation and identification of sparse systems. For each problem, we propose new adaptive solutions by integrating the sparsity information to the classical methods in order to improve their performance. Numerical simulations have been conducted to confirm the superiority of the proposed methods compared to the state of the art
Liu, Yi-Cheng, and 劉奕成. "Application of Covariance Driven Stochastic Subspace Identification Method." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/33712859772337110292.
國立臺灣大學
土木工程學研究所
99
In this research the application of output-only system identification technique known as Stochastic Subspace Identification (SSI) algorithms in civil structures is carried out. With the aim of finding accurate modal parameters of the structure in off-line analysis, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data matrix. A sensitivity study of the implementation of SSI through stabilization diagram is firstly carried out, different scenarios such as noise effect, nonlinearity, time-varying systems and closely-spaced frequencies are considered. Comparison between different SSI approaches was also discussed. In the following, the identification task of a real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures is carried out, for which the capacity of Covariance-driven SSI algorithm (SSI-COV) will be demonstrated. The introduction of a subspace preprocessing algorithm known as Singular Spectrum Analysis (SSA) can greatly enhance the identification capacity, which in conjunction with SSI-COV is called the SSA-SSI-COV method, it also allows the determination of the best system order. The objective of the second part of this research is to develop on-line system parameter estimation and damage detection technique through Recursive Covariance-driven Stochastic Subspace identification (RSSI-COV) approach. The Extended Instrumental Variable version of Projection Approximation Subspace Tracking algorithm (EIV-PAST) is taking charge of the system-related subspace updating task. To further reduce the noise corruption in field experiments, the data pre-processing technique called recursive Singular Spectrum Analysis technique (rSSA) is developed to remove the noise contaminant measurements, so as to enhance the stability of data analysis. Through simulation study as well as the experimental research, both RSSI-COV and rSSA-SSI-COV method are applied to identify the dynamic behavior of systems with time-varying characteristics, the reliable control parameters for the model are examined. Finally, these algorithms are applied to track the evolution of modal parameters for: (1) shaking table test of a 3-story steel frame with instantaneous stiffness reduction. (2) Shaking table test of a 1-story 2-bay reinforced concrete frame, both under earthquake excitation, and at last, (3) damage detection and early warning of an experimental steel bridge under continuous scour.
Lin, Chiung-Chin, and 林炅嶔. "Subspace Method for Blind Channel Identification with Unknown Channel Order." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/n347kc.
國立交通大學
電機與控制工程系所
92
Subspace method for blind channel identification of communication channels usually require that the channel order is known. This requirement is not realistic in practice. We propose algorithms for the determination of channel order, when only an upper bound of the channel order is known, so that the subspace method can be used for channel identification.
KUMAR, VIPIN. "A STUDY ON ELECTROMECHANICAL MODE ESTIMATION OF POWER SYSTEM BY SUBSPACE IDENTIFICATION METHOD." Thesis, 2018. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16251.
HUANG, TENG-YI, and 黃騰毅. "Application of Subspace Identification Method on Dynamic System Modeling of Machine Tool and Evaluation of Cutting Performance." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/se8vzf.
國立中正大學
機械工程系研究所
107
The motivation of the dissertation is to develop intelligent manufacturing system of the machine tool and to build the virtual machine tool model based on the industrial 4.0 production mode. The dynamic model which integrates servo interpolation, machine structure, and feed drive system is proposed and the cutting dynamics is also included to investigate vibration suppression and contour error estimation of the machining trajectory. In building the electrical system, not only the servo control but also the nonlinear friction effect is included simultaneously. In establishing the feed drive system, the paper adopts a novel experimental approach instead of using a non-traditional theoretical derivation. The approach is to capture the signal from the interpolator which could compute the path acceleration and deceleration, corner deceleration and other information with synchronous measurement of the acceleration of the working platform using the accelerometer. By applying the subspace system identification method (SIM), the structural and axis driving characteristics of the feed drive system can be realized in the virtual dynamic model. By testing different trajectories using different interpolation parameters, it shows that the subspace model can accurately predict the vibration of the XY table with the RMS (root mean square) error being less than 20%. The further approach is to measure the axis position and the relative position between the spindle tool center (TCP) and platform by the KGM such that the TCP dynamic response and the contour of the cutting path can be evaluated. Besides of building the complete dynamic model, the dissertation also investigates the cutting force simulation and the mechanism of chatting. By integrating the structural, transmission, servo and cutting dynamics, it is wished that the geometric accuracy of workpiece could be predicted. Furthermore, the parameters of interpolator are optimized such that the machining time can be minimized under the given contour errors.
Lee, How-Ping, and 李灝平. "Blind Identification of MIMO Systems Using Fast Kurtosis Maximization Algorithm and a Second-Order Statistics Based Subspace Method." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/35017127022244387682.
國立清華大學
通訊工程研究所
91
Blind identification (BID) of multiple input multiple output systems is purposed to estimate an unknow system by using only the measurements. In general, the approaches of BID can be partitioned into two categories─ second-order statistics based algorithms, and higher-order statistics based algorithms. The advantages of second-order statistics based algorithms are shorter data lenght requirement, existence of closed form solution while the disadvantages are sensitivity to noise, requirement of prior imformation about channel lengths, more restrictions on systems. The advantages of higher-order statistics based algorithms are insensitivity to noise, less restrictions on systems, while the disadvantages are longer data length requirement, high computational load. Gorokhov and Loubaton have proposed a second-order statistics based subspace method for blind identification of an unknown K-input P-output (P either larger than or equal to K and K larger than 1) FIR system with the K input signals being mutually independent and temporally independent identically distributed (i.i.d.). However, only a partial system estimate can be obtained using their method. That is, the system estimate will be the unknown system multiplied an unknown ambiguity matrix R(z). In the case of equal channels, R(z) will be a constant nonsingular matrix and in the case of different channel lengths, R(z) will be a nonsingular upper triangular matrix. This thesis is concerned with resolving the ambiguity matrix R(z) embedded in the system estimate obtained by Gorokhov and Louba-ton’s subspace method. An approach is proposed in this thesis by utilizing Chi and Chen’s fast kurtosis maximization algorithm to estimate the inverse of the ambiguity matrix; meanwhile, the unknown system can thus be perfectly identified.
Wang, Sheng-Wei, and 王勝威. "An Improved Stochastic Subspace Identification Method Based on Alternative Stabilization Diagram and Hierarchical Sifting Process for Applications in Several Types of Civil Structures." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/56531512683909950024.
國立雲林科技大學
工程科技研究所
104
This study first establishes a new methodology based on the covariance type of stochastic subspace identification for extensively identifying the modal parameters of a stay cable. Several details of choosing the parameters in performing SSI are examined. An important discovery is that the lower limit for setting the time lag parameter can be decided by the ratio of the fundamental period of cable to the sampling time increment for a valid identification with the conventional stabilization diagram. Inspired by the above criterion, an alternative stabilization diagram is further proposed to more conveniently distinguish stable modal parameters of cable. A hierarchical process with three stages of sifting is then developed to systematically and automatically extract reliable modal parameters from the alternative stabilization diagram. Demonstrated by analyzing the ambient vibration measurements for three stay cables of Chi-Lu Bridge, the feasibility of the new methodology is verified with successfully obtaining the modal frequencies, damping ratios, and mode shape ratios for almost all the cable modes in the examined frequency range. The same approach is then generalized to the applications in other types of civil structures such as bridge decks or buildings. The measurements from different types of structures are systematically investigated to extend the applicability of the newly discovered criterion for the time lag parameter to ensure stable identification results. Such a criterion is first validated for its applications with single measurements from stay cables, bridge decks, and buildings. Regarding multiple measurements, it is found that the predicted threshold works well for the cases of stay cables and buildings, but makes an evident overestimation for the case of bridge decks. This discrepancy is further explained by the fact that the deck vibrations are induced by multiple excitations independently coming from the passing traffic. In addition, the computation efficiency of the alternative stabilization diagram is also explored to certify that appropriate down sampling can be applied to significantly reduce the computational cost without losing accuracy. Finally, the improved SSI algorithm developed in this study is further applied to investigate several sets of known and blind monitoring data from Ting Kau Bridge under different wind excitation conditions for assessing a benchmark problem launched to explore its mode identifiability. The evaluation of delicately selected cases clearly distinguishes the effect of traffic excitation on the identifiability of the targeted deficient mode from the effect of wind excitation. An additional upper limit for the vertical acceleration amplitude at deck, mainly induced by the passing traffic, is subsequently suggested to supplement the previously determined lower limit for the wind speed. The analysis incorporating the tower measurements solidly verifies that the deficient mode is actually induced by the motion of the central tower. Moreover, it is also confirmed that this mode can be stably identified under all the circumstances with the addition of tower measurements.