Relevant bibliographies by topics / Nonlinear Estimation / Dissertations / Theses
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Dissertations / Theses on the topic 'Nonlinear Estimation'

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Published: 4 June 2021
Last updated: 26 July 2025

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1

Reynard, D. M. "Nonlinear estimation." Thesis, University of Newcastle Upon Tyne, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336142.

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2

Sugathevan, Suranthiran. "Nonlinear and distributed sensory estimation." Diss., Texas A&M University, 2003. http://hdl.handle.net/1969.1/2246.

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Methods to improve performance of sensors with regard to sensor nonlinearity, sensor noise and sensor bandwidths are investigated and new algorithms are developed. The necessity of the proposed research has evolved from the ever-increasing need for greater precision and improved reliability in sensor measurements. After describing the current state of the art of sensor related issues like nonlinearity and bandwidth, research goals are set to create a new trend on the usage of sensors. We begin the investigation with a detailed distortion analysis of nonlinear sensors. A need for efficient disto
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3

Sayyaddelshad, Saleh. "State estimation of nonlinear systems." Licentiate thesis, Luleå tekniska universitet, Signaler och system, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-25774.

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Observer design for nonlinear systems is a popular problem in control theory that has beenstudied from many angles. Since the system state variables, in general, are not available, stateestimation is essential in many control applications, which is why the problem is so attractivefor researchers. One example of a process that has nonlinear dynamics is wood drying.In the wood drying process, there are some unmeasurable variables such as the moisturecontent at the surface and inside the wood, which are important for controlling the drying processfor the purpose of minimizing the energy consumpti
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4

Aslan, Serdar. "Nonlinear Estimation Techniques Applied To Econometric." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605649/index.pdf.

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This thesis considers the filtering and prediction problems of nonlinear noisy econometric systems. As a filter/predictor, the standard tool Extended Kalman Filter and new approaches Discrete Quantization Filter and Sequential Importance Resampling Filter are used. The algorithms are compared by using Monte Carlo Simulation technique. The advantages of the new algorithms over Extended Kalman Filter are shown.
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5

Stamnes, Øyvind Nistad. "Nonlinear Estimation with Applications to Drilling." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for teknisk kybernetikk, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-12500.

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This thesis addresses the topic of nonlinear estimation and its applications. Particular emphasis is given to downhole pressure estimation for Managed Pressure Drilling (MPD), but due to the mathematical similarities of the two problems, velocity estimation for mechanical systems is also considered.  The thesis consists of the following three parts:Part I of this thesis addresses the problem of pressure estimation for MPD systems. Over the last decade MPD has emerged as a tool for drilling offshore wells with tight pressure margins. Several technologies for MPD have been developed and this the
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6

McGinnity, Shaun Joseph. "Nonlinear estimation techniques for target tracking." Thesis, Queen's University Belfast, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263495.

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7

Misawa, Eduardo Akira. "Nonlinear state estimation using sliding observers." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14549.

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8

Wei, Jianfeng. "Observation and Estimation of Nonlinear Systems." Case Western Reserve University School of Graduate Studies / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=case1143611470.

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9

Hurtig, Juliet K. "Parameter set estimation for nonlinear systems /." The Ohio State University, 1999. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488191124571832.

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10

Sardonini, Laura <1979&gt. "Invariants estimation in nonlinear time series." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/381/1/PhDThesis-Sardonini.pdf.

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11

Sardonini, Laura <1979&gt. "Invariants estimation in nonlinear time series." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/381/.

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12

De, Ruiter Anton. "Nonlinear state-estimation for spacecraft attitude determination." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ62888.pdf.

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13

Bellaire, Robert Louis. "Nonlinear estimation with applications to target tracking." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/15399.

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14

Darvish, Hossein. "Smart Power Grid Synchronization with Nonlinear Estimation." Thesis, Southern Illinois University at Edwardsville, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1589157.

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<p> Grid synchronization is a critical concern for proper control of energy transfer between the Distributed Power Generation Systems (DPGS) and the utility power grid. Nonlinear estimation techniques are proposed to track the voltage magnitude, phase angle, and frequency of the utility grid. Instead of directly analyzing in abc coordinate frame, the symmetrical component is employed to separate the positive, negative, and zero sequences in the transformed AlphaBeta stationary coordinate frame. By using the Fortescue's Transformations and Clarke's Transformation, the number of system state var
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15

Wang, Zhao. "Nonlinear estimation and control for assistive robots." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5089.

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In this thesis, we document the progress in the estimation and control design of a smart assistive robot arm that can provide assistance during activities of daily living to the elderly and/or users with disabilities. Interaction with the environment is made challenging by the kinematic uncertainty in the robot, imperfect sensor calibration, limited view of angle as well as the fact that most activities of daily living are generally required to be performed in unstructured environments. For monocular visual systems, range (or depth) information is always crucial for target modeling and system
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16

MAGRI, RAFAEL RIBEIRO. "NONLINEAR ERROR CORRECTION MODELS: ESTIMATION AND TESTING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2010. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34955@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO<br>Testes existentes para não-linearidade em Modelos de Correção de Erros são altamente intensivos computacionalmente e apresentam parâmetros de estorvo na distribuição assintótica, que precisam ser levantadas através de simulações por bootstrap. É proposto um teste consistente, implementável em qualquer pacote estatístico e que apresenta distribuição assintótica Qui-Quadrado. Além disso, experimentos de Monte Carlo mostra
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17

Pakki, Bharani Chandra Kumar. "Nonlinear state estimation algorithms and their applications." Thesis, University of Leicester, 2013. http://hdl.handle.net/2381/27950.

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State estimation is a process of estimating the unmeasured or noisy states using the measured outputs and control inputs along with process and measurement models. The extended Kalman filter (EKF) has been an important approach for nonlinear state estimation over the last five decades. However, EKFs are only suitable for ‘mild’ nonlinearities where the first-order approximations of the nonlinear functions are available and they also require evaluation of state and measurement Jacobians at every iteration. This thesis presents a few linear and nonlinear state estimation methods and their applic
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18

Kim, Hag-Soo. "Semiparametric estimation of nonlinear simultaneous equations models." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1273662774.

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19

Codd, Casey L. "Nonlinear Structural Equation Models: Estimation and Applications." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1301409131.

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20

Aslan, Serdar Supervisor :. Demirbaş Kerim. "Nonlinear estimation techniques applied to econometric problems." Ankara : METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605649/index.pdf.

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21

Osgood, Elizabeth. "Nonlinear surface approximation using photogammetry." Texas A&M University, 2005. http://hdl.handle.net/1969.1/3314.

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Many satellite applications require a model that represents a surface as it deforms over time. Yet, space applications demand a precise, low-weight, low-volume, and easy to implement solution. A metrology sensing system is presented in this thesis, consisting of a series of cameras and laser dot projectors positioned along the length of the antenna. This system accurately models the geometry of the surface to meet the demands of a space based radar. Each laser dot projector casts a matrix of points onto the antenna surface. The points are then imaged simultaneously by a pair of cameras, each h
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22

Altmann, Yoann. "Nonlinear unmixing of Hyperspectral images." Phd thesis, Toulouse, INPT, 2013. http://oatao.univ-toulouse.fr/10588/1/altmann.pdf.

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Spectral unmixing is one the major issues arising when analyzing hyperspectral images. It consists of identifying the macroscopic materials present in a hyperspectral image and quantifying the proportions of these materials in the image pixels. Most unmixing techniques rely on a linear mixing model which is often considered as a first approximation of the actual mixtures. However, the linear model can be inaccurate for some specific images (for instance images of scenes involving multiple reflections) and more complex nonlinear models must then be considered to analyze such images. The aim of
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23

Schön, Thomas B. "Estimation of Nonlinear Dynamic Systems : Theory and Applications." Doctoral thesis, Linköpings universitet, Reglerteknik, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7124.

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This thesis deals with estimation of states and parameters in nonlinear and non-Gaussian dynamic systems. Sequential Monte Carlo methods are mainly used to this end. These methods rely on models of the underlying system, motivating some developments of the model concept. One of the main reasons for the interest in nonlinear estimation is that problems of this kind arise naturally in many important applications. Several applications of nonlinear estimation are studied. The models most commonly used for estimation are based on stochastic difference equations, referred to as state-space models. T
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24

Forssén, Patrik. "Adsorption Isotherm Parameter Estimation in Nonlinear Liquid Chromatography." Doctoral thesis, Uppsala universitet, Avdelningen för teknisk databehandling, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5971.

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This thesis concerns the development and validation of methods for the industrially important area of adsorption isotherm parameter estimation in preparative, nonlinear high performance liquid chromatography (HPLC). Preparative chromatography is a powerful separation method to get pure compounds from more or less complex liquid mixtures, e.g., mixtures of mirror-image molecules. Computer simulations can be used to optimize preparative chromatography, but then competitive adsorption isotherm parameters are usually required. Here two methods to estimate adsorption isotherm parameters are treated
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25

Schön, Thomas B. "Estimation of Nonlinear dynamic systems : theory and applications /." Linköping : Univ, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7124.

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26

Forssén, Patrik. "Adsorption isotherm parameter estimation in nonlinear liquid chromatography /." Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5971.

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27

SHIKANO, Kiyohiro, Fumitada ITAKURA, Kazuya TAKEDA, Hiroshi SARUWATARI, and Hidekazu KAMIYANAGIDA. "Direction of Arrival Estimation Using Nonlinear Microphone Array." Institute of Electronics, Information and Communication Engineers, 2001. http://hdl.handle.net/2237/15048.

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28

Baldacchino, Tara. "Statistical estimation and identification of nonlinear dynamic systems." Thesis, University of Sheffield, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548536.

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29

Chen, Boli. "Nonlinear adaptive estimation with application to sinusoidal identification." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/28964.

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Parameter estimation of a sinusoidal signal in real-time is encountered in applications in numerous areas of engineering. Parameters of interest are usually amplitude, frequency and phase wherein frequency tracking is the fundamental task in sinusoidal estimation. This thesis deals with the problem of identifying a signal that comprises n (n ≥ 1) harmonics from a measurement possibly affected by structured and unstructured disturbances. The structured perturbations are modeled as a time-polynomial so as to represent, for example, bias and drift phenomena typically present in applications, wher
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30

Tobenkin, Mark M. "Nonlinear filtering for narrow-band time delay estimation." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53166.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.<br>Includes bibliographical references (p. 101-103).<br>This thesis presents a method for improving passive acoustic tracking. A large family of acoustic tracking systems combine estimates of the time difference of arrival (TDoA) between pairs of spatially separated sensors - this work improves those estimates by independently tracking each TDoA using a Bayesian filter. This tracking is particularly useful for overcoming spatial aliasing, which results from tracking narrowband,
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31

Zhu, Ting F. (Ting Fredrick). "Estimation of nonlinear mechanical properties of atherosclerotic plaques." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33907.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.<br>Includes bibliographical references (leaves 57-59).<br>A numerical method has been developed to estimate the mechanical properties of atherosclerotic plaques by combining genetic algorithm with finite element methods. Plaque images derived from optical coherence tomography were employed to construct finite element models which were subsequently used in conjunction with a genetic algorithm to determine the parameters in a nonlinear constitutive model. A new multi-frame scheme is introduced to better
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32

Dhingra, Jastej S. "Estimation of nonlinear systems using Jump Matrix Technique." Thesis, Virginia Tech, 1988. http://hdl.handle.net/10919/43844.

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33

Creveling, Daniel R. "Parameter and state estimation in nonlinear dynamical systems." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3336421.

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Thesis (Ph. D.)--University of California, San Diego, 2008.<br>Title from first page of PDF file (viewed December 16, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 122-124).
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34

Ljungberg, Fredrik. "Estimation of Nonlinear Greybox Models for Marine Applications." Licentiate thesis, Linköpings universitet, Reglerteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165828.

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As marine vessels are becoming increasingly autonomous, having accurate simulation models available is turning into an absolute necessity. This holds both for facilitation of development and for achieving satisfactory model-based control. When accurate ship models are sought, it is necessary to account for nonlinear hydrodynamic effects and to deal with environmental disturbances in a correct way. In this thesis, parameter estimators for nonlinear regression models where the regressors are second-order modulus functions are analyzed. This model class is referred to as second-order modulus mode
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35

Sando, Simon Andrew. "Estimation of a class of nonlinear time series models." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15985/1/Simon_Sando_Thesis.pdf.

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The estimation and analysis of signals that have polynomial phase and constant or time-varying amplitudes with the addititve noise is considered in this dissertation.Much work has been undertaken on this problem over the last decade or so, and there are a number of estimation schemes available. The fundamental problem when trying to estimate the parameters of these type of signals is the nonlinear characterstics of the signal, which lead to computationally difficulties when applying standard techniques such as maximum likelihood and least squares. When considering only the phase data, we also
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36

Sando, Simon Andrew. "Estimation of a class of nonlinear time series models." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15985/.

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The estimation and analysis of signals that have polynomial phase and constant or time-varying amplitudes with the addititve noise is considered in this dissertation.Much work has been undertaken on this problem over the last decade or so, and there are a number of estimation schemes available. The fundamental problem when trying to estimate the parameters of these type of signals is the nonlinear characterstics of the signal, which lead to computationally difficulties when applying standard techniques such as maximum likelihood and least squares. When considering only the phase data, we also
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37

Loudermilk, Margaret Susan. "Estimation and testing in dynamic, nonlinear panel data models." Diss., Connect to online resource - MSU authorized users, 2006.

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38

Chew, Alvin. "Accuracy driven adaptive nonlinear analysis of planar framed structures." Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248367.

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39

Covello, James Anthony. "Nonlinear Bounded-Error Target State Estimation Using Redundant States." Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195557.

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When the primary measurement sensor is passive in nature--by which we mean that it does not directly measure range or range rate--there are well-documented challenges for target state estimation. Most estimation schemes rely on variations of the Extended Kalman Filter (EKF), which, in certain situations, suffer from divergence and/or covariance collapse. For this and other reasons, we believe that the Kalman filter is fundamentally ill-suited to the problems that are inherent in target state estimation using passive sensors. As an alternative, we propose a bounded-error (or set-membership)
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40

Sawo, Felix. "Nonlinear state and parameter estimation of spatially distributed systems." Karlsruhe Univ.-Verl. Karlsruhe, 2009. http://d-nb.info/994500211/04.

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41

Oh, Seung-Min. "Nonlinear Estimation for Vision-Based Air-to-Air Tracking." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19882.

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Unmanned aerial vehicles (UAV's) have been the focus of significant research interest in both military and commercial areas since they have a variety of practical applications including reconnaissance, surveillance, target acquisition, search and rescue, patrolling, real-time monitoring, and mapping, to name a few. To increase the autonomy and the capability of these UAV's and thus to reduce the workload of human operators, typical autonomous UAV's are usually equipped with both a navigation system and a tracking system. The navigation system provides high-rate ownship states (typically ownshi
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42

Lee, Deok-Jin. "Nonlinear bayesian filtering with applications to estimation and navigation." Texas A&M University, 2004. http://hdl.handle.net/1969.1/2269.

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In principle, general approaches to optimal nonlinear filtering can be described in a unified way from the recursive Bayesian approach. The central idea to this recur- sive Bayesian estimation is to determine the probability density function of the state vector of the nonlinear systems conditioned on the available measurements. However, the optimal exact solution to this Bayesian filtering problem is intractable since it requires an infinite dimensional process. For practical nonlinear filtering applications approximate solutions are required. Recently efficient and accurate approximate non- l
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43

Yang, Yin. "Nonlinear control and state estimation of holonomic indoor airship." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=106573.

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Three full-state optimal controllers are proposed to fulfill the requirements of flying an indoor holonomic airship in real-time, namely, hovering control, set-point control and continuous reference tracking. In the hovering control design, the airship is assumed to be a quasi stationary plant, and an infinite horizon linear quadratic regulator (LQR) operating in again scheduling manner is employed. Meanwhile, a controller based on the state-dependent Riccati equation (SDRE) and ad hoc feedforward compensation is synthesized to tackle the set-point control problem. Lastly, a continuous tracker
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44

Ponomareva, Ksenia. "Latent state estimation in a class of nonlinear systems." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/6519.

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The problem of estimating latent or unobserved states of a dynamical system from observed data is studied in this thesis. Approximate filtering methods for discrete time series for a class of nonlinear systems are considered, which, in turn, require sampling from a partially specified discrete distribution. A new algorithm is proposed to sample from partially specified discrete distribution, where the specification is in terms of the first few moments of the distribution. This algorithm generates deterministic sigma points and corresponding probability weights, which match exactly a specified
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45

Cuellar, Sanchez Milena Clarissa. "Perspectives and advances in parameter estimation of nonlinear models." Thesis, London School of Economics and Political Science (University of London), 2007. http://etheses.lse.ac.uk/2712/.

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Nonlinear methodologies to estimate parameters of deterministic nonlinear models are investigated in the case where experimental observations are available and uncertainty sources are present, e.g. model inadequacy, model error and noise. The problem of parameter estimation is interpreted from a nonlinear dynamical time series analysis perspective; however deterministic and probabilistic techniques originated outside the nonlinear deterministic framework are studied, implemented and discussed. Conceptually, the Thesis is divided in two parts that explore two fundamentally different approaches:
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46

Lopez, Negrete de la Fuente Rodrigo. "Nonlinear Programming Sensitivity Based Methods for Constrained State Estimation." Research Showcase @ CMU, 2011. http://repository.cmu.edu/dissertations/174.

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Model based control schemes, such as nonlinear model predictive control, assume that the full state vector of the plant is known for feedback control. However, in reality this is not always true. Most times only a set of noisy measurements are available, and thus, the unmeasured states need to be inferred from these measurements. This is done in combination with a detailed model of the system. The most common nonlinear state estimation methods do not have a means to deal with bounds or constraints on the states in an efficient or systematical way. These bounds and constraints are important in
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47

Gilitschenski, Igor [Verfasser]. "Deterministic Sampling for Nonlinear Dynamic State Estimation / Igor Gilitschenski." Karlsruhe : KIT Scientific Publishing, 2016. http://www.ksp.kit.edu.

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48

Mercieca, Julian. "Estimation of temporal and spatio-temporal nonlinear descriptor systems." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/19416/.

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As advances in the remote sensing of fluid flows forge ahead at an impressive rate, we face an increasingly compelling question of how best to exploit this progress. Light detection and ranging (LIDAR) measurement equipment still presents the problems of having only radial (line-of-sight) wind speed measurements (Cyclops' dilemma). Substantial expanses of unmeasured flow still remain and range weighting errors have a considerable influence on LIDAR measurements. Clearly, more information needs to be extracted from LIDAR data and an estimation problem naturally arises. A key challenge is that m
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49

Azarbayejani, Ali J. "Nonlinear probabilistic estimation of 3-D geometry from images." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/29122.

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50

Lawson, W. Gregory 1975. "Probabilistic state estimation in regimes of nonlinear error growth." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/30291.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2005.<br>Includes bibliographical references (p. 273-286).<br>State estimation, or data assimilation as it is often called, is a key component of numerical weather prediction (NWP). Nearly all implementable methods of state estimation suitable for NWP are forced to assume that errors remain in regimes of linear error growth and retain distributions of Gaussian uncertainty, yet nonlinear systems like the atmosphere can readily allow regimes of nonlinear error growth and, in turn, produce
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