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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Volterra Systems with Realizable Kernels

Nguyen, Hoan Kim Huynh 30 April 2004 (has links)
We compare an internal state method and a direct Runge-Kutta method for solving Volterra integro-differential equations and Volterra delay differential equations. The internal state method requires the kernel of the Volterra integral to be realizable as an impulse response function. We discover that when applicable, the internal state method is orders of magnitude more efficient than the direct numerical method. However, constructing state representation for realizable kernels can be challenging at times; therefore, we propose a rational approximation approach to avoid the problem. That is, we approximate the transfer function by a rational function, construct the corresponding linear system, and then approximate the Volterra integro-differential equation. We show that our method is convergent for the case where the kernel is nuclear. We focus our attention on time-invariant realizations but the case where the state representation of the kernel is a time-variant linear system is briefly discussed. / Ph. D.
2

Network Reconstruction and Vulnerability Analysis of Financial Networks

Woodbury, Nathan Scott 01 May 2017 (has links)
Passive network reconstruction is the process of learning a structured (networked) representation of a dynamic system through the use of known information about the structure of the system as well as data collected by observing the inputs into a system along with the resultant outputs. This work demonstrates an improvement on an existing network reconstruction algorithm so that the algorithm is capable of consistently and perfectly reconstructing a network when system inputs and outputs are measured without error. This work then extends the improved network reconstruction algorithm so that it functions even in the presence of noise as well as the situation where inputs into the system are unknown. Furthermore, this work demonstrates the capability of the new extended algorithms by reconstructing financial networks from stock market data, and then performing an analysis to understand the vulnerabilities of the reconstructed network to destabilization through localized attacks. The creation of these improved and extended algorithms has opened many theoretical questions, paving the way for future research into network reconstruction.
3

Redukcija dinamičkih modela elektroenergetskog sistema primenom teorije balansnih realizacija i aproksimativnih bisimulacionih relacija i funkcija / Reduction of power system dynamic models based on the balanced realization theory and approximate bisimulation relations and functions

Đukić Savo 14 March 2014 (has links)
<p>Disertacijom su opisane postojeće tehnike redukcije dinamičkih modela koje se koriste u teoriji upravljanja i postojeće tehnike za redukciju dinamičkih modela i ekvivalentiranje elektroenergetskih sistema. Predložen je nov pristup na fizici problema zasnovanoj redukciji dinamičkog modela elektroenergetskog sistema korišćenjem teorije balansnih realizacija. Takođe se predlaže korišćenje aproksimativnih bisimulacionih relacija za redukciju dinamičkih modela elektroenergetskog sistema. Postojeće tehnike i predloženi pristupi i algoritmi su primenjeni za redukciju dinamičkih modela dva razmatrana test sistema.</p> / <p>Dissertation describes the existing dynamic model reduction techniques used in control theory and existing techniques that are used for the reduction (equivalencing) of power system dynamic models. A new approach to physics-based reduction of power system dynamic model based on the balanced realization theory is proposed. Use of approximate bisimulation relations for reduction of power system dynamic models is also proposed. Existing techniques and proposed approaches and algorithms are applied to reduce the dynamic models of two considered test systems.<br />&nbsp;</p>
4

Dynamic melodic expectancy

Aarden, Bret J. 14 October 2003 (has links)
No description available.
5

Minimality, input-output equivalence and identifiability of LPV systems in state-space and linear fractional representations / Minimalité, équivalence entrée-sortie et identifiabilité des systèmes LPV sous forme d’état et sous forme de représentations linéaires fractionaires

Alkhoury, Ziad 09 November 2017 (has links)
Dans cette thèse, plusieurs concepts importants liés à la théorie de la réalisation des modèles linéaires à paramètres variants (LPV) sont étudiés.Tout d’abord, nous abordons le problème de l’identifiabilité des modèles LPV affines (ALPV). Une nouvelle condition suffisante et nécessaire est introduite afin de garantir l’identifiabilité structurelle pour les paramétrages ALPV. L’identifiabilité de cette classe de paramétrages est liée à l’absence d’isomorphismes liant deux représentations d’état LPV lorsque deux modèles LPV correspondant à différentes valeurs des variables de séquencement sont considérés. Nous présentons ainsi une condition suffisante et nécessaire pour l’identifiabilité structurelle locale, et une condition suffisante pour l’identifiabilité structurelle (globale) qui sont toutes deux fonction du rang d’une matrice définie par l’utilisateur. Ces dernières conditions permettent la vérification de l’identifiabilité structurelle des modèles ALPV.Ensuite, étant donné que les techniques d’identification dites locales sont parfois inévitables, nous fournissons une expression analytique de la borne supérieure de l’erreur de comportements entrées-sorties de deux modèles LPV équivalents localement. Cette erreur se révèle être une fonction de (i) la vitesse de changement du signal de séquencement et (ii) l’écart entre les bases cohérentes de deux modèles LPV. En particulier, la différence entre les sorties des deux modèles peut être arbitrairement réduite en choisissant un signal de séquencement qui varie assez lentement.Enfin, nous présentons et étudions des propriétés importantes de la transformation des représentations d’état ALPV en Représentations Linéaires Fractionnelles (LFR). Plus précisément, nous montrons que (i) les représentations ALPV minimales conduisent à des LFR minimales, et vice versa, (ii) le comportement entrée-sortie de la représentation ALPV détermine de manière unique le comportement entrée-sortie de la LFR résultante, (iii) les modèles ALPV structurellement identifiables fournissent des LFRs structurellement identifiables et vice versa. Nous caractérisons ensuite les LFRs qui correspondent á des modèles ALPV équivalents basés sur leurs applications entrées-sorties. Comme illustré tout au long du manuscrit, ces résultats ont des conséquences importantes pour l’identification et la commande des systèmes LPV. / In this thesis, important concepts related to the identification of Linear Parameter-Varying (LPV) systems are studied.First, we tackle the problem of identifiability of Affine-LPV (ALPV) state-space parametrizations. A new sufficient and necessary condition is introduced in order to guarantee the structural identifiability for ALPV parameterizations. The identifiability of this class of parameterizations is related to the lack of state-space isomorphisms between any two models corresponding to different scheduling parameter values. In addition, we present a sufficient and necessary condition for local structural identifiability, and a sufficient condition for (global) structural identifiability which are both based on the rank of a model-based matrix. These latter conditions allow systematic verification of structural identifiability of ALPV models. Moreover, since local identification techniques are inevitable in certain applications, it is thus a priority to study the discrepancy between different LPV models obtained using different local techniques. We provide an analytic error bound on the difference between the input-output behaviors of any two LPV models which are frozen equivalent. This error bound turns out to be a function of both (i) the speed of the change of the scheduling signal and (ii) the discrepancy between the coherent bases of the two LPV models. In particular, the difference between the outputs of the two models can be made arbitrarily small by choosing a scheduling signal which changes slowly enough.Finally, we introduce and study important properties of the transformation of ALPV statespace representations into Linear Fractional Representations (LFRs). More precisely, we show that (i) state minimal ALPV representations yield minimal LFRs, and vice versa, (ii) the inputoutput behavior of the ALPV representation determines uniquely the input-output behavior of theresulting LFR, (iii) structurally identifiable ALPV models yield structurally identifiable LFRs, and vice versa. We then characterize LFRs which correspond to equivalent ALPV models based on their input-output maps. As illustrated all along the manuscript, these results have important consequences for identification and control of LPV systems.
6

Metodologia para identificação de sistemas em espaço de estados por meio de excitações pulsadas. / Methodology for identifying state space systems by means of pulsed excitations.

LIMA, Rafael Bezerra Correia. 30 July 2018 (has links)
Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-07-30T14:13:06Z No. of bitstreams: 1 RAFAEL BEZERRA CORREIA LIMA - TESE PPGEE 2016..pdf: 2324960 bytes, checksum: db1b63193864e8e19bcba191952df2b9 (MD5) / Made available in DSpace on 2018-07-30T14:13:06Z (GMT). No. of bitstreams: 1 RAFAEL BEZERRA CORREIA LIMA - TESE PPGEE 2016..pdf: 2324960 bytes, checksum: db1b63193864e8e19bcba191952df2b9 (MD5) Previous issue date: 2016-09-20 / Nesse trabalho são apresentadas contribuições na área de identificação de sistemas representados em espaço de estados. E proposta uma metodologia completa para estimação de modelos que representem as principais dinâmicas de processos industriais. O fluxo natural das procedimentos de identificação consiste da coleta experimental dos dados, seguido pela escolha dos modelos candidatos e da utilização de um critério de ajuste que selecione o melhor modelo possível. Nesse sentido é proposta uma metodologia para estimativa de modelos em espaço de estados, utilizando excitações pulsadas. A abordagem desenvolvida combina algoritmos precisos e eficientes com experimentos rápidos, adequados a ambientes industriais. O projeto das excitações é realizado em tempo real, por meio de informações coletadas em um curto experimento inicial, baseado em uma única oscilação de uma estrutura realimentada por um relê. Esse mecanismo possibilita uma estimativa preliminar do atraso e da constante de tempo dominante do sistema. O método de identificação proposto é baseado na teoria de realizações de Kalman. É apresentada uma reformulação do problema de realizações clássico, para comportar sinais de entrada pulsados. Essa abordagem se mostra computacionalmente eficiente, assim como apresenta resultados semelhantes aos métodos de benehmark. A técnica possibilita também a estimativa de atrasos de transporte e a inserção de conhecimentos prévios por meio de um problema de otimização com restrições via LMI Linear Matrix Incqualities. Em muitos casos, somente as características principais do sistema são relevantes em um projeto de sistema de controle. Portanto é proposta uma técnica para obtenção de modelos de primeira ordem com atraso, a partir da redução de modelos balanceados em espaço de estados. Por fim, todas as contribuições discutidas nesse trabalho de tese são validadas em uma série de plantas experimentais em escala de laboratório. Plantas essas, projetadas e construídas com o intuito de emular o cotidiano operacional de instalações industriais reais. / This work Íntroduces contributions related to thc field of systems identification of state space models. It is proposed a complete methodology for modei estimation that encompasses the main dynamics of industrial processes. The natural flxix of the identification procedures rests on the the empirical collection of data followed by the choice of candidate modela and posterior use ot an adjusting criteria that drafts the best model amoug the contenders. In this sense. a uew methodology is proposed for models estimation in state spaces using pulsed excitation signal. The developed approach combines accurate and efhcient algorithms with quick experíments whose are suitable for the industrial environment. The excitatiou design is performed in real time by means of information collected in a snort mitíai experíment based in an single oscillation of a relay feedback. This mechanism allows a preliminary estimation of both delay and time constant prevalent in the system. The identification method proposed is based on Kalmairs realization theory. The thesis íntroduces a reformulation of the classic realization problem so it can admit pulsed input signals. This approaíth show itself as computationally efficient as well as provides similar results eompared to those obtained when perfonning the benchmark methods. Moreover, the technic allows the transport delay estimation and insertion of prior knowledge by means of an optimization problem with restrictions via linear matrix inequalities restrictions. In many cases only the characteristics of the main system are relevant in control systems design. Therefore a technique for the attainment first order models with time delay based on balanced state space models reduction. Lastly ali the contributions provided aíong the thesis are discussed and validated in a series of pilot scale plants. designed and built to emulate the operational cycle in real industrial plants.
7

Necessary and Sufficient Informativity Conditions for Robust Network Reconstruction Using Dynamical Structure Functions

Chetty, Vasu Nephi 03 December 2012 (has links) (PDF)
Dynamical structure functions were developed as a partial structure representation of linear time-invariant systems to be used in the reconstruction of biological networks. Dynamical structure functions contain more information about structure than a system's transfer function, while requiring less a priori information for reconstruction than the complete computational structure associated with the state space realization. Early sufficient conditions for network reconstruction with dynamical structure functions severely restricted the possible applications of the reconstruction process to networks where each input independently controls a measured state. The first contribution of this thesis is to extend the previously established sufficient conditions to incorporate both necessary and sufficient conditions for reconstruction. These new conditions allow for the reconstruction of a larger number of networks, even networks where independent control of measured states is not possible. The second contribution of this thesis is to extend the robust reconstruction algorithm to all reconstructible networks. This extension is important because it allows for the reconstruction of networks from real data, where noise is present in the measurements of the system. The third contribution of this thesis is a Matlab toolbox that implements the robust reconstruction algorithm discussed above. The Matlab toolbox takes in input-output data from simulations or real-life perturbation experiments and returns the proposed Boolean structure of the network. The final contribution of this thesis is to increase the applicability of dynamical structure functions to more than just biological networks by applying our reconstruction method to wireless communication networks. The reconstruction of wireless networks produces a dynamic interference map that can be used to improve network performance or interpret changes of link rates in terms of changes in network structure, enabling novel anomaly detection and security schemes.

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