Tesi sul tema "States estimation"
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1
Covello, James Anthony. "Nonlinear Bounded-Error Target State Estimation Using Redundant States". Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195557.
Abstract (sommario):
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) approach to the target state estimation problem. Such estimators are nearly as old as the Kalman filter, but have enjoyed much less attention. In this study we develop a practical estimator that bounds the target states, and apply it to the two-dimensional case of a submarine tracking a surface vessel, which is commonly referred to as Target Motion Analysis (TMA). The estimator is robust in the sense that the true target state does not escape the determined bounds; and the estimator is not unduly pessimistic in the sense that the bounds are not wider than the situation dictates. The estimator is--as is the problem itself--nonlinear and geometric in nature. In part, the simplicity of the estimator is maintained by using redundant states to parameterize the target's velocity. These redundant states also simplify the incorporation of other measurements that are frequently available to the system. The estimator's performance is assessed in a series of simulations and the results are analyzed. Extensions of the algorithm are considered.
2
Song, Hui. "Real time feedback control using predictive states estimation". Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/27041.
Abstract (sommario):
In this thesis, we present a real time feedback control strategy to optimize the dynamic performance of computer communication network. In previous studies [8-10], feedback delay, arising from communication delay, was shown to degrade system performance. Considering this negative impact of delay, we propose a new control law which predicts, in advance, the traffic and exercises control based on the predicted traffic.
In experiments, we apple the token bucket (TB) mechanism to construct a discrete dynamic system model [8-10], in which one multiplexor, linked to all the TBs, multiplexes the conforming traffic that have been policed at TBs. We demonstrate that the improvement of the system performance by presenting the simulation results corresponding to different stochastic traffic models. The experiments and analysis in this thesis provide valuable insight for the network researchers to do traffic optimal control [35].
3
Streff, Michael J. "The estimation of United States Army reenlistment rates". Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/25902.
4
Lewis, Clayton S. "Evapotranspiration Estimation: A Study of Methods in the Western United States". DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4683.
Abstract (sommario):
This research focused on estimating evapotranspiration (i.e., the amount of water vaporizing into the atmosphere through processes of surface evaporation and plant transpiration) under both theoretical and actual conditions. There were two study areas involved: one, on a large scale where 704 agriculturally-representative, electronic weather stations were used to evaluate the drivers and calculated reference evapotranspiration of a NASA gridded weather forcing model in the 17 western states in the contiguous U.S.; and two, transpiration of invasive saltcedar (Tamarix sp.) in the floodplain of the lower Colorado River, California, with Bowen ratio, eddy covariance, and groundwater fluxes. In this study, a fire destroyed the saltcedar forest, which allowed comparison of evapotranspiration before and after\ this event
Comparison of the input weather parameters showed some variance between the electronic weather stations and the gridded model, but calculated reference evapotranspiration performed well by relying on the better input and more highly weighed variables of air temperature and downward shortwave radiation. Only in the southern portions of California, Arizona, and New Mexico were the evapotranspiration estimates using the gridded dataset not well correlated with the electronic weather stations and not recommended for prediction. Saltcedar evapotranspiration was found to match more recent and conservative estimates for the phreatophyte than what was historically portrayed in the literature. Horizontal advection from the surrounding desert was also observed to affect the riparian energy balance. Annual average total evapotranspiration before a fire varied from 0.60-1.44 meters/year to 0.25-1.00 meters/year post fire.
5
Doyle, Mary Anne. "Youth vs. experience in the enlisted Air Force productivity estimation and policy analysis /". Santa Monica, CA : Rand, 1998. http://books.google.com/books?id=BIvfAAAAMAAJ.
6
Dasso, Michael W. "Analysis of the United States Hop Market". DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1419.
Abstract (sommario):
Hops are one of the four main ingredients used to produce beer. Many studies have been done to analyze the science behind growing and harvesting hops, creating hop hybrids, and how to brew beer with hops. However, there has been little research done revolving around the economic demand and supply model of the hop market. The objectives of this study are to create an econometric model of supply and demand of hops in the United States from 1981 to 2012, and to identify important exogenous variables that explain the supply and demand of hops using the two-stage least squares (2SLS) method of analysis. Using the 2SLS method, the demand model yielded that the US beer production variable is significant at the 10 percent level. For every 1 percent change in US beer production, there will be a 6.25 percent change in quantity of hops demanded in the same direction. The supply model showed that US acreage is significant at the 1 percent level. For every 1 percent change in US acreage, there will be a 0.889 percent change in quantity of hops supplied in the same direction. The implications of this study are viewed in relation to both producers and consumers.
7
Al-Rawahy, Khalid Hilal. "Embodied consumption of U.S. copper and sulfur: Implications for intensity of use estimation and forecasting". Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185277.
Abstract (sommario):
Domestic mineral consumption is defined as a net sum of apparent consumption plus embodied mineral contained in net imported goods. The U.S. is a net importer of copper-containing products, such as automobiles, electrical products, and construction and industrial machinery. Embodied copper which is contained in net imports of these products constitute part of domestic copper consumption. On the other hand, the U.S. is a net exporter of sulfur-using/embodying products, such as fertilizers and grains. The sulfur which is contained/employed in manufacturing exported products is not actually part of domestic sulfur consumption. Net embodied U.S. imports (exports) of copper (sulfur) are estimated. For copper, it is shown that domestic U.S. consumption is understated and increasing, intensity of use is constant rather than decreasing, and, in general, forecast increases in domestic consumption of copper are due mainly to embodied copper imports. For sulfur, it is shown that domestic consumption is overstated and declining; domestic intensity of use is also declining. The domestic copper and sulfur industries will be differentially impacted as a result of this increased reliance on overseas markets.
8
Iossifov, Plamen K. "Estimation of United States money demand functions using longitudinal family-level data". Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 192Mb, 133 p, 2005. http://wwwlib.umi.com/dissertations/fullcit/3181862.
9
Gursoy, Gonenc. "Neural Network Based Online Estimation Of Maneuvering Steady States And Control Limits". Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612147/index.pdf.
Abstract (sommario):
This thesis concerns the design and development of neural network based predictive algorithms to predict approaching aircraft limits. Therefore, approximate dynamics of flight envelope parameters such as angle of attack and load factor are constructed using neural network augmented dynamic models. Then, constructed models are used to predict steady state responses. By inverting the models and solving for critical controls at the known envelope limits, critical control inputs are calculated as well. The performance of the predictor algorithm
is then evaluated with a different neural network online adaptation law which uses a stack of recorded data. It is shown that using a stack of recorded data online, constructed models become much more representative of limit parameter dynamics compared to adaptation using instantaneous measured data only. The benefits of recording data online and using it for weight adaptation are presented in the scope of dynamic trim and control limit predictions.
10
Happ, Christof J. [Verfasser]. "Adaptive and Non-Adaptive Estimation of Discrete Quantum States / Christof J. Happ". München : Verlag Dr. Hut, 2013. http://d-nb.info/104287820X/34.
11
Ghassempour, Aghamolki Hossein. "Phasor Measurement Unit Data-based States and Parameters Estimation in Power System". Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6505.
Abstract (sommario):
The dissertation research investigates estimating of power system static and dynamic states (e.g. rotor angle, rotor speed, mechanical power, voltage magnitude, voltage phase angle, mechanical reference point) as well as identification of synchronous generator parameters. The research has two focuses:
i. Synchronous generator dynamic model states and parameters estimation using real-time PMU data.
ii.Integrate PMU data and conventional measurements to carry out static state estimation.
The first part of the work focuses on Phasor Measurement Unit (PMU) data-based synchronous generator states and parameters estimation. In completed work, PMU data-based synchronous generator model identification is carried out using Unscented Kalman Filter (UKF). The identification not only gives the states and parameters related to a synchronous generator swing dynamics but also gives the states and parameters related to turbine-governor and primary and secondary frequency control. PMU measurements of active power and voltage magnitude, are treated as the inputs to the system while voltage phasor angle, reactive power, and frequency measurements are treated as the outputs. UKF-based estimation can be carried out at real-time. Validation is achieved through event play back to compare the outputs of the simplified simulation model and the PMU measurements, given the same input data. Case studies are conducted not only for measurements collected from a simulation model, but also for a set of real-world PMU data. The research results have been disseminated in one published article.
In the second part of the research, new state estimation algorithm is designed for static state estimation. The algorithm contains a new solving strategy together with simultaneous bad data detection. The primary challenge in state estimation solvers relates to the inherent non-linearity and non-convexity of measurement functions which requires using of Interior Point algorithm with no guarantee for a global optimum solution and higher computational time. Such inherent non-linearity and non-convexity of measurement functions come from the nature of power flow equations in power systems.
The second major challenge in static state estimation relates to the bad data detection algorithm. In traditional algorithms, Largest Normalized Residue Test (LNRT) has been used to identify bad data in static state estimation. Traditional bad data detection algorithm only can be applied to state estimation. Therefore, in a case of finding any bad datum, the SE algorithm have to rerun again with eliminating found bad data. Therefore, new simultaneous and robust algorithm is designed for static state estimation and bad data identification.
In the second part of the research, Second Order Cone Programming (SOCP) is used to improve solving technique for power system state estimator. However, the non-convex feasible constraints in SOCP based estimator forces the use of local solver such as IPM (interior point method) with no guarantee for quality answers. Therefore, cycle based SOCP relaxation is applied to the state estimator and a least square estimation (LSE) based method is implemented to generate positive semi-definite programming (SDP) cuts. With this approach, we are able to strengthen the state estimator (SE) with SOCP relaxation. Since SDP relaxation leads the power flow problem to the solution of higher quality, adding SDP cuts to the SOCP relaxation makes Problem’s feasible region close to the SDP feasible region while saving us from computational difficulty associated with SDP solvers. The improved solver is effective to reduce the feasible region and get rid of unwanted solutions violate cycle constraints. Different Case studies are carried out to demonstrate the effectiveness and robustness of the method.
After introducing the new solving technique, a novel co-optimization algorithm for simultaneous nonlinear state estimation and bad data detection is introduced in this dissertation. ${\ell}_1$-Norm optimization of the sparse residuals is used as a constraint for the state estimation problem to make the co-optimization algorithm possible. Numerical case studies demonstrate more accurate results in SOCP relaxed state estimation, successful implementation of the algorithm for the simultaneous state estimation and bad data detection, and better state estimation recovery against single and multiple Gaussian bad data compare to the traditional LNRT algorithm.
12
Li, Xinyu. "Size-Structured Population Model with Distributed States in The Recruitment| Approximation and Parameter Estimation". Thesis, University of Louisiana at Lafayette, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10163274.
Abstract (sommario):
We consider a size-structured population model where individuals may be recruited into the population at different sizes. First and second order finite difference schemes are developed to approximate the solution of the model. The convergence of the approximations to a unique weak solution is proved. We then show that as the distribution of the new recruits become concentrated at the smallest size, the weak solution of the distributed states-at-birth model converges to the weak solution of the classical Sinko-Streifer type size-structured model in the weak* topology. Numerical simulations are provided to demonstrate the achievement of the desired accuracy of the two methods for smooth solutions as well as the superior performance of the second-order method in resolving solution-discontinuities. A least-squares method is developed for estimating parameters in a size-structured population model with distributed states-at-birth from field data. The first and second order finite difference schemes for approximating solution of the model are utilized in the least-squares problem. Convergence results for the computed parameters are established. Numerical results demonstrating the efficiency of the technique are provided.
13
Haverland, R. L., D. F. Post, L. R. Cooper e E. D. Shirley. "Estimation of Soil Texture and Plant Available Water by Correlation with the Laser Light-Scattering Method". Arizona-Nevada Academy of Science, 1985. http://hdl.handle.net/10150/296363.
Abstract (sommario):
From the Proceedings of the 1985 Meetings of the Arizona Section - American Water Resources Association and the Hydrology Section - Arizona-Nevada Academy of Science - April 27, 1985, Las Vegas, Nevada
14
Valdez-Zamudio, Diego, e D. Phillip Guertin. "Soil Erosion Estimation in the Sonoyta River Watershed Using the USLE and Remote Sensing and GIS Techniques". Arizona-Nevada Academy of Science, 1996. http://hdl.handle.net/10150/297019.
15
Saksena, Michelle J. "Three Essays on the Social Science of Obesity". The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1405893684.
16
Jiang, Kun. "Real-time estimation and diagnosis of vehicle's dynamics states with low-cost sensors in different driving condition". Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2292/document.
Abstract (sommario):
Le développement des systèmes intelligents pour contrôler la stabilité du véhicule et éviter les accidents routier est au cœur de la recherche automobile. L'expansion de ces systèmes intelligents à l'application réelle exige une estimation précise de la dynamique du véhicule dans des environnements diverses (dévers et pente). Cette exigence implique principalement trois problèmes : ⅰ), extraire des informations non mesurées à partir des capteurs faible coût; ⅱ), rester robuste et précis face aux les perturbations incertaines causées par les erreurs de mesure ou de la méconnaissance de l'environnement; ⅲ), estimer l'état du véhicule et prévoir le risque d'accident en temps réel. L’originalité de cette thèse par rapport à l’existant, consiste dans le développement des nouveaux algorithmes, basés sur des nouveaux modèles du véhicule et des différentes techniques d'observation d'état, pour estimer des variables ou des paramètres incertains de la dynamique du véhicule en temps réel. La première étape de notre étude est le développement de nouveaux modèles pour mieux décrire le comportement du véhicule dans des différentes situations. Pour minimiser les erreurs de modèle, un système d'estimation composé de quatre observateurs est proposé pour estimer les forces verticales, longitudinales et latérales par pneu, ainsi que l'angle de dérive. Trois techniques d'observation non linéaires (EKF, UKF et PF) sont appliquées pour tenir compte des non-linéarités du modèle. Pour valider la performance de nos observateurs, nous avons implémenté en C++ des modules temps-réel qui, embarqué sur le véhicule, estiment la dynamique du véhicule pendant le mouvementEnhancing road safety by developing active safety system is the general purpose of this thesis. A challenging task in the development of active safety system is to get accurate information about immeasurable vehicle dynamics states. More specifically, we need to estimate the vertical load, the lateral frictional force and longitudinal frictional force at each wheel, and also the sideslip angle at center of gravity. These states are the key parameters that could optimize the control of vehicle's stability. The estimation of vertical load at each tire enables the evaluation of the risk of rollover. Estimation of tire lateral forces could help the control system reduce the lateral slip and prevent the situation like spinning and drift out. Tire longitudinal forces can also greatly influence the performance of vehicle. The sideslip angle is one of the most important parameter to control the lateral dynamics of vehicle. However, in the current market, very few safety systems are based on tire forces, due to the lack of cost-effective method to get these information. For all the above reasons, we would like to develop a perception system to monitor these vehicle dynamics states by using only low-cost sensor. In order to achieve this objective, we propose to develop novel observers to estimate unmeasured states. However, construction of an observer which could provide satisfactory performance at all condition is never simple. It requires : 1, accurate and efficient models; 2, a robust estimation algorithm; 3, considering the parameter variation and sensor errors. As motivated by these requirements, this dissertation is organized to present our contribution in three aspects : vehicle dynamics modelization, observer design and adaptive estimation. In the aspect of modeling, we propose several new models to describe vehicle dynamics. The existent models are obtained by simplifying the vehicle motion as a planar motion. In the proposed models, we described the vehicle motion as a 3D motion and considered the effects of road inclination. Then for the vertical dynamics, we propose to incorporate the suspension deflection to calculate the transfer of vertical load. For the lateral dynamics, we propose the model of transfer of lateral forces to describe the interaction between left wheel and right wheel. With this new model, the lateral force at each tire can be calculated without sideslip angle. Similarly, for longitudinal dynamics, we also propose the model of transfer of longitudinal forces to calculate the longitudinal force at each tire. In the aspect of observer design, we propose a novel observation system, which is consisted of four individual observers connected in a cascaded way. The four observers are developed for the estimation of vertical tire force, lateral tire force and longitudinal tire force and sideslip angle respectively. For the linear system, the Kalman filter is employed. While for the nonlinear system, the EKF, UKF and PF are applied to minimize the estimation errors. In the aspect of adaptive estimation, we propose the algorithms to improve sensor measurement and estimate vehicle parameters in order to stay robust in presence of parameter variation and sensor errors. Furthermore, we also propose to incorporate the digital map to enhance the estimation accuracy. The utilization of digital map could also enable the prediction of vehicle dynamics states and prevent the road accidents. Finally, we implement our algorithm in the experimental vehicle to realize real-time estimation. Experimental data has validated the proposed algorithm
17
Tamayao, Mili-Ann Maguigad. "Urbanization and Vehicle Electrification in the United States: Life Cycle CO2 Emissions Estimation and Climate Policy Implications". Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/483.
Abstract (sommario):
Recent sustainability research has focused on urban systems given their high share of environmental impacts and potential for centralized impact mitigation. Most previous works rely on descriptive statistics obtained from place-based case studies representing major cities, metropolitan areas, and counties using emissions inventories that may have inconsistent and/or limited scope (e.g., transportation and residential emissions only). This limits the potential for general insights and decision support related to the role of urbanization in CO2 emissions reduction. Here, I implement generalized linear and multiple linear regression analyses to obtain robust insights on the relationship between urbanization and CO2 emissions in the U.S. I used consistently derived county-level scope 1 & 2 CO2 inventories for my response variable while predictor variables included dummy-coded variables for county geographic type (central, outlying, and non-metropolitan), median household income, population density, and climate indices (heating degree days (HDD) and cooling degree days (CDD)). There is statistically significant difference in per capita emissions by sector for different county types, with transportation and residential emissions highest in nonmetropolitan (rural) counties, transportation emissions lowest in central (most urbanized) counties, and commercial sector emissions highest in central counties. More importantly, contrary to most previous findings, there is not enough statistical evidence indicating that per capita scope 1 & 2 emissions differ by geographic type, ceteris paribus. These results are robust for different assumed electricity emissions factors. Given that emissions production rate in more urban counties are not significantly different from that of less urban ones and population is concentrated in urban counties, significant national emissions reduction could be achieved if efforts are focused on central counties. There are various climate mitigation techniques – both from the supply and demand side. Given the large contribution of transportation in total county emissions and the fact that this technology bridges the transportation and electricity sector which is currently the biggest contributor to CO2 emissions, I investigated the emission reduction benefits from driving electric instead of gasoline vehicles. Vehicle electrification has also received sustained support from the local to the supranational level and is seeing an optimistic market trend. I characterize and assess the uncertainty in CO2 emissions per mile travelled for vehicles in the U.S. given regional variation and uncertainty in electricity emissions factor (marginal vs average, generation- vs consumption-based, different regional boundaries), driving pattern, and daily vehicle miles traveled (DVMT). I also investigate vehicle emissions estimates under convenience (vehicle starts charging when it arrives at home) and delayed (vehicle starts charging at 12am) charging. Using marginal emissions factors results in electric vehicle emissions estimate that are higher than average emissions estimates in the northeastern and north central U.S., and lower emissions in the south central U.S. In other regions, using marginal emissions versus average emissions factors may lead to differences in emissions estimates by as much as 28%. Delayed charging leads to higher emissions, given that off-peak electricity demand is supplied by fossil generators in most regions (e.g., coal). Using marginal emissions estimates, the Nissan Leaf electric vehicle has lower operation emissions compared to the Toyota Prius (the most efficient US gasoline vehicle) in western U.S., and the Leaf has higher operation emissions in the north central, regardless of assumed charging scheme and estimation method. In other regions the comparison is uncertain because of regional variation and uncertainty in emission factor estimates. Consumption- and generation-based marginal emissions also significantly (5 % - 28%), enough to result unclear comparison results. Average vehicle emissions estimates under different regional boundary definitions also differ significantly (e.g., state-based estimates deviate from National Electricity Reliability Commission (NERC) region-based estimates by as much as 122%). Other factors such as driving pattern and daily vehicle miles traveled also influence vehicle emissions. I conduct a locational comparison of electric and gasoline vehicle life cycle emissions in the U.S. taking into consideration the regional variation in the joint effect of consumption-based marginal electricity emission factors, driving pattern (city, highway or combined), and daily vehicle miles traveled (DVMT) distribution. I find that electricity generation emissions rate, determined by grid mix and charging scheme, has the largest influence on electric vehicle emission levels and the emissions differences of gasoline and electric vehicles. Secondary to this is urbanization level, especially for PHEVs, as it influences driving pattern and daily vehicle miles traveled. Highest CO2 emission reductions from electric vehicles can be attained in metropolitan counties in CA, TX, FL, NY, and New England states. Policies for wider adoption of electric vehicles such as incentives and other adoption facilitating mechanisms including investments in public charging infrastructure are encouraged in metropolitan counties, especially the denser ones. On the other hand, these policies are discouraged in north central states where electric vehicles would only increase emissions because of a relatively carbon-intensive grid. These findings reflect the pivotal role of the electricity and transportation sectors nexus in achieving national goals of CO2 emission reductions. Unless the U.S. decarbonizes its electricity system further, electric vehicles will only be beneficial in climate mitigation efforts in certain locations in the country.
18
Laurent, Quentin. "Estimation and prediction of wave input and system states based on local hydropressure and machinery response measurements". Thesis, KTH, Optimeringslära och systemteori, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191995.
Abstract (sommario):
Waves represent a big untapped energy source and many are endeavouring to develop Wave Energy Converters (WEC) to harvest this resource. The goal of this thesis, carried out with the young technology company CorPower Ocean AB, is to enable a better control of the company’s WEC by providing control strategies with a prediction of the input force on the device, also called excitation force. Previous work is already available for wave prediction, but this time the time-series we need to predict is not available and we used instead some pressure, force and position measurements to determine the value of the force in the future. The time-series of the measurements are linked to the values of the force thanks to linear (airy) wave theory and some linearisation of the existent model for the forces applied on the WECs. Three methods were suggested: prediction using an AR model then transformation thanks to transfer functions, Kalman filtering and Wiener filtering. The two latter have a better, more or less equivalent performance in terms of Mean Square Error, but the focus was made on the Wiener filter since it didn’t require identification under the assumption of a JONSWAP spectrum for the waves. This last method was implemented in the Simulink model of CorPowerOcean and extensively tested to quantify the influence of a variation in the sea state, noise conditions or parameters of the filter. The prediction were however rarely above 60% for a half wave period in the future and use of the method as is for non-causal control is questionable. We conclude by giving some other potential solutions for pursuing work in this domain.
19
Soriano, Melissa. "Estimation of soil moisture in the southern united states in 2003 using multi-satellite remote sensing measurements". Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3361.
Abstract (sommario):
Thesis (M.S.)--George Mason University, 2008.Vita: p. 65. Thesis director: John Qu. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Earth System Science. Title from PDF t.p. (viewed Jan. 11, 2009). Includes bibliographical references (p. 59-64). Also issued in print.
20
Shamsi, Mohammad Haris. "Analysis of an electric Equivalent Circuit Model of a Li-Ion battery to develop algorithms for battery states estimation". Thesis, Uppsala universitet, Elektricitetslära, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-298427.
Abstract (sommario):
Batteries have imparted momentum to the process of transition towards a green future. However, mass application of batteries is obstructed due to their explosive nature, a trait specific to Li-Ion batteries. To cater to an efficient battery utilization, an introduction of a battery management system would provide an ultimate solution. This thesis deals with different aspects crucial in designing a battery management system for high energy as well as high power applications. To build a battery management system capable of predicting battery behavior, it is necessary to analyze the dynamic processes happening inside the battery. Hence, a battery equivalent circuit model is proposed in this thesis as well as proper analysis is done in MATLAB to project a generic structure applicable to all Li-Ion chemistries. The model accounts for all dynamic characteristics of a battery including non-linear open circuit voltage, discharge current and capacity. Effect of temperature is also modeled using a cooling system. The model is validated with test current profiles. Less than 0.1% error between measured and simulated voltage profiles indicates the effectiveness of the proposed model to predict the runtime behavior of the battery. Furthermore, the model is implemented with the energy as well as the power battery pack. State of charge calculations are performed using the proposed model and the coulomb counting method and the results indicate only a 4% variance. Therefore, the proposed model can be applied to develop a real-time battery management system for accurate battery states estimation.
21
Ritz, Alison. "Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States". Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104108.
Abstract (sommario):
Remote sensing offers many advantages to previous forest measurements, such as limiting costs and time in the field. Light detection and ranging (lidar) has been shown to enable accurate estimates of forest height. Lidar does produce precise measurements for ground elevation and forest height, where and when it is available. However, it is expensive to collect and does not have wall-to-wall coverage in the United States. In this study, we estimated height using the National Agricultural Imagery Program (NAIP) photogrammetric point clouds to create a predicted height map for managed loblolly pine stands in the southeastern United States. Recent studies have investigated the ability of digital aerial photogrammetry (DAP), and more specifically NAIP, as an alternative to lidar as a means of estimating forest height due to its lower costs, frequency of acquisition, and wall-to-wall coverage across the United States. Field-collected canopy height for 534 plots in Virginia and North Carolina were regressed against the 90th percentile derived from NAIP point clouds. The model for predicted pine height using the 90th percentile of height (P90) is predicted pine height = 1.09(P90) – 0.43. The adjusted R^2 is 0.93, and the RMSE is 1.44 m. This model is being used to produce a 5 m x 5 m canopy height model for all pine stands across Virginia, North Carolina, and Tennessee. NAIP-derived point clouds are thus a viable means of predicting canopy height in southern pines.M.S.
Collecting accurate measurements of pine plantations is essential to managing them to maximize various ecosystem goods and services. However, it can be difficult and time-consuming to collect these measurements by hand. This study demonstrates that point clouds derived from digital stereo aerial photograms enable calculating forest height to an accuracy sufficient for pine plantation management. We developed a simple linear regression model to predict forest canopy height using the 90th percentile of the photo-derived heights above the ground in a given area. With this model, we created a map of pine plantation canopy heights (consisting of 5 m x 5 m grid cells, each containing a canopy height estimate) for pine forests in Virginia, North Carolina, and Tennessee. Digital aerial photography from the National Agricultural Imagery Program (NAIP) is repeated every three years for a given state, allowing growth to be mapped over time. Photography collected by NAIP and similar programs also has uniform acquisition parameters in a given year applicable over large regions. State- and national photography programs like NAIP are also less expensive than other data sets, like airborne laser scanning data, that enable estimation of tree height.
22
Souza, Douglas Delgado de 1987. "Informação quântica com estados coerentes comprimidos da luz". [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276940.
Abstract (sommario):
Orientador: Antonio Vidiella BarrancoTese (doutorado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin
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Resumo: Na primeira parte deste trabalho seguimos os estudos de Hirota e colaboradores e definimos quatro estados quase-Bell baseados em estados coerentes comprimidos da luz. Dois desses estados são maximamente emaranhados, enquanto o emaranhamento dos outros dois depende apenas da sobreposição entre os estados coerentes comprimidos que os compõem. A partir destes estados quase-Bell, definimos novos estados interpolados cujo emaranhamento é também governado por um parâmetro de interpolação adicional e estudamos algumas das propriedades destes estados (emaranhamento e eficiência energética). Por fim, usamos estes estados e definimos alguns estados de Werner, com os quais analisamos de forma simples uma possível influência de um ambiente dissipativo parametrizado pela probabilidade de o estado de Werner estar em sua forma emaranhada ou misturada. Para esta análise usamos os conceitos de separabilidade e emaranhamento. Na segunda parte estudamos a estimativa de fase quântica usando estados gaussianos puros (estados coerentes comprimidos). Iniciamos com a estimativa da fase introduzida por um operador unitário em cujo hamiltoniano está presente uma perturbação linear nos operadores de criação e aniquilação, além do operador de número de fótons responsável pela evolução de fase (perturbação linear unitária). Obtemos quais são os estados gaussianos ótimos para a estimativa desta fase e analisamos a optimalidade da detecção homódina. A seguir, consideramos o parâmetro de perturbação como uma variável aleatória que obedece a uma distribuição gaussiana de probabilidades (perturbação linear aleatória) e novamente obtemos os estados de sonda ótimos e analisamos a optimalidade da detecção homódina. Por fim, estudamos a estimativa de fase com perturbação linear unitária utilizando os estados quase-Bell interpolados definidos na primeira parte deste trabalho e verificamos que a utilização de emaranhamento permite uma melhor estimativa de fase para uma mesma energia disponível
Abstract: In the first part of this work we follow the studies of Hirota and collaborators and we define four quasi-Bell states based on squeezed coherent states of light. Two of these states are maximally entangled, while the entanglement of the other two depends only on the overlap between the squeezed coherent states that were combined. From these quasi-Bell states we define new interpolated states for which the entanglement is also governed by an additional interpolation parameter, and we study some of the properties of these states (entanglement and energy efficiency). Finally, we use these states to define some Werner states, which we use to study in a simple way the possible influence of some dissipative environment parameterized by the probability that the Werner state is entangled or mixed. For this analysis we use the concepts of separability and entanglement. In the second part, we study the quantum phase estimation using pure Gaussian states (squeezed coherent states). We begin with the estimation of the phase introduced by a unitary operator whose Hamiltonian also contains a disturbance that is linear in the creation and annihilation operators in addition to the photon number operator responsible for the phase evolution (unitary linear disturbance). We find what are the optimal Gaussian states for this phase estimation and we also analyze the optimality of the homodyne detection. Next, we consider the disturbance parameter to be a random variable submitted to a Gaussian distribution (random linear disturbance) and again we find what are the optimal probe states and analyze the optimality of the homodyne detection. Finally we study the phase estimation with unitary linear disturbance using the interpolated quasi-Bell states defined in the first part of this work and we verify that the use of entanglement leads to a better phase estimation for the same amount of available energy
Doutorado
Física
Doutor em Ciências
2011/00220-5
FAPESP
23
Dotson, Meryle Akeara. "Postnatal Dental Mineralization: a Comparative Analysis of Dental Development Among Contemporary Populations of the Southeastern United States". Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3079.
Abstract (sommario):
Due to the strong genetic component of dental development, research has shown that mineralization patterns of the human dentition are relatively buffered against environmental influences that normally affect bone growth and development. It is because of this resistance to environmental factors and the continuous growth of the permanent dentition throughout childhood and adolescence that the evaluation of dental development patterns has become the preferred method of age estimation in living and deceased children.
Researchers (Harris and Mckee 1990; Tompkins 1996; Blankenship et al. 2007; Kasper et al. 2009) have suggested that the timing of dental development varies by ancestral descent and geographic populations. However, further evaluations of these perceived differences in the timing of dental development among populations are necessary as classical statistical methods result in age estimations that are biased toward the age structure of the reference population. However, the Bayesian approach is beneficial since it incorporates relevant prior knowledge into the analysis and formalizes the relationship between assumptions and conclusions (Buck et al. 1996). Therefore, the purpose of this research is to incorporate methods in Bayesian analysis to compare the timing of dental development between two contemporary populations of the Southeastern United States, as well as test the accuracy of dental development age parameters devised by Moorrees et al. (1963) on a contemporary Florida Population.
For this study, 51 panoramic radiographs of individuals from a contemporary Florida population ranging in age from 7.7-20.4 years were reviewed. Statistical analyses incorporated a Bayesian approach to compare the timing of dental development for individuals comprising the contemporary Florida sample with the timing of dental development for a contemporary Middle Tennessee population by utilizing the age structure of the Middle Tennessee population as informed prior knowledge, otherwise referred to as an informed prior. Transition distributions for age, given stage of dental development, were also modeled for individuals comprising the contemporary Florida sample. The accurate observation and comparison of probability density distributions for age can serve as a noninvasive method for evaluating the probability of whether or not an unknown individual is a particular age, given the stage of dental development.
Results of this research indicate that there is a consistent underestimation of age for individuals comprising the contemporary Florida population when the age structure of the Middle Tennessee population is utilized as an informed prior. Additionally, the results of this thesis indicate that there is a consistent underestimation of age when utilizing age parameters of Moorrees et al. (1963) for the estimation of age for individuals from a contemporary Florida population. By incorporating a Bayesian approach to compare two contemporary populations of the Southeastern United States, a comprehensive analysis of the relationship between age and stage of dental development can be achieved. Therefore, the results of this thesis support Bayesian analysis as an appropriate method of evaluating perceived differences in the timing of dental development between contemporary populations. Furthermore, the results of this research are beneficial to the field of forensic anthropology as the observation of advanced stages of molar development utilizing panoramic radiographs serves as a noninvasive method in estimating age for unknown juveniles and young adults, and can also assist courts within the United States in determining whether or not an individual is legally considered a minor or an adult.
24
Fischer, Manfred M., Florian Huber, Michael Pfarrhofer e Petra Staufer-Steinnocher. "The dynamic impact of monetary policy on regional housing prices in the United States". WU Vienna University of Economics and Business, 2018. http://epub.wu.ac.at/6658/1/2018%2D11%2D16_housing_favar_(002).pdf.
Abstract (sommario):
This paper uses a factor-augmented vector autoregressive model to examine the impact of monetary
policy shocks on housing prices across metropolitan and micropolitan regions. To simultaneously
estimate the model parameters and unobserved factors we rely on Bayesian estimation
and inference. Policy shocks are identified using high-frequency suprises around policy
announcements as an external instrument. Impulse reponse functions reveal differences in regional
housing price responses, which in some cases are substantial. The heterogeneity in policy
responses is found to be significantly related to local regulatory environments and housing supply
elasticities. Moreover, housing prices responses tend to be similar within states and adjacent
regions in neighboring states.Series: Working Papers in Regional Science
25
Xiaolong, Luo. "Natechs and Climate Change：Wide-scale Spatial Modeling of the Occurrence Probability and Variability of Tropical Storm-Related Natech Events in the United States Under Various Climate Scenarios". Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263631.
Abstract (sommario):
京都大学新制・課程博士
博士(工学)
甲第23170号
工博第4814号
京都大学大学院工学研究科都市社会工学専攻
(主査)教授 CRUZ Ana Maria , 教授 宇野 伸宏, 准教授 横松 宗太
学位規則第4条第1項該当
Doctor of Philosophy (Engineering)
Kyoto University
DFAM
26
Williams, David Richard. "Estimation of black and white housing services demand elasticities in the United States using a simultaneous model of tenure choice and housing services demand". Gainesville, FL, 1986. http://www.archive.org/details/estimationofblac00will.
27
Zekraoui, Salim. "Contrôle et estimation en temps fini de certaines classes d'EDP". Electronic Thesis or Diss., Centrale Lille Institut, 2023. http://www.theses.fr/2023CLIL0028.
Abstract (sommario):
L'objectif principal de cette thèse est d'explorer et d'analyser les problèmes d'estimation et destabilisation non-asymptotique (en temps fini, fixe, et prescrit) de certaines classes de systèmes de dimensioninfinie, notamment les systèmes linéaires invariants en temps avec retards (ponctuels ou distribués) d'entrée oude sortie et les équations aux dérivées partielles (EDP) de type réaction-diffusion. Comme les résultats existantssur ces classes de systèmes sont peu nombreux, nous commençons par revoir les concepts et les résultats sur lesoutils non asymptotiques pour les systèmes de dimension infinie. Ensuite, nous étendons ces outils pour les systèmesde dimension infinie. Dans ce contexte, nous commençons par le problème de compensation, en temps fini/fixe,des retards d'entrée et de sortie pour les systèmes LTI en utilisant la méthode du backstepping pour les EDP(avec des transformations inversibles non-linéaires et/ou variant en temps). Pour appliquer cette approche, nousreformulons le système considéré en une cascade de système EDO-EDP où la partie EDP est une équation detransport hyperbolique qui modélise l'effet du retard sur l'entrée/sortie. Ensuite, nous traitons le problème dela stabilisation frontière en temps fini/fixe d'une classe des EDP de réaction-diffusion. À notre connaissance,ce problème est resté ouvert dans la littérature pendant une période considérable. Nous abordons ce problèmecomplexe à l'aide de méthodes classiques liées aux Fonctions de Lyapunov de Contrôle (CLF). Nous donnonsquelques indications sur l'extension de cette approche au problème de stabilisation entrée-état (ISS) et au problèmedu suivi en temps fini/fixe pour les EDP de réaction-diffusion. Nous soulignons les limitations de notre méthodepour la conception des observateurs. Enfin, nous abordons le problème de la compensation, en temps prescrit, desretards d'entrée des systèmes de réaction-diffusion par une commande par retour d'état basée sur un observateur enutilisant la méthode du backstepping pour les EDP. Ce problème est difficile, car il nécessite de traiter la conceptiondes observateurs et des contrôleurs avec des gains variant en temps qui tendent vers l'infini lorsque le temps serapproche du temps prescrit de convergenceThis Ph.D. thesis is devoted to the problems of non-asymptotic (finite, fixed, prescribed-time) estimation and stabilization of some classes of infinite-dimensional systems, namely LTI systems subject to input/sensor (pointwise or distributed) delays and reaction-diffusion PDEs. As the existing results on these classes of systems are few, we begin by reviewing relevant concepts and results on non-asymptotic tools (including homogeneity-based tools and time-varying tools) for finite-dimensional systems. Afterward, we extend these tools to infinite-dimensional settings. Firstly, we start with the problem of input and sensor delay compensation in finite/fixed/prescribed time of LTI systems where we use the so-called backstepping approach for PDEs (with some nonlinear and/or time-varying invertible transformations). To apply this approach, we reformulate the considered LTI system into a cascade ODE-PDE system where the PDE part is a hyperbolic transport equation that models the effect of the delay on the input/output. Secondly, we consider the problem of boundary state-dependent finite/fixed-time stabilization of reaction-diffusion PDEs. To the best of our knowledge, this problem has remained open in the literature for a considerable long time. We tackle this challenging problem using classical methods related to Control Lyapunov functions. We provide some hints on how we to extend this approach to input-to-state stabilization and non-asymptotic tracking problem for reaction-diffusion PDEs. We point out the limitations of our approach to observer design. Finally, we tackle the problem of input delay compensation of reaction-diffusion systems in prescribed time by output feedback using the backstepping approach. This problem is challenging, as one deals with observer and control designs with some time-varying gains that go to infinity when the time gets closer to the prescribed time of convergence, which brings additional challenges and issues. Dealing with these challenges requires introducing novel infinite-dimensional time-varying backstepping transformations in conjunction with advanced predictor-based concepts adapted to parabolic PDEs
28
Zheng, Yue. "Valuation of country of origins of organic processed food: a comparative study of consumer demand for soymilk in the United States and China". Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/8634.
Abstract (sommario):
Master of ScienceDepartment of Agricultural Economics
Xianghong Li
Hikaru H. Peterson
The organic food market in the United States expanded rapidly at annual rates between 12% and 21% from 1997 to 2008, yet the adoption rate of organic farming remained stagnant. Industry sources suggest that the degree of outsourcing organic inputs has been increasing during the most recent years. Organic foods are available at traditional supermarkets and mass merchandisers. Many retailers now offer organic food products in their private labels. This study focuses on organic soymilk, which illustrates these recent trends. China, a major low income country which supplies organic agricultural ingredients to the U.S. , has raised food safety concerns fueled by recent incidents. Organic foods have been marketed in China as eco-products in an effort to promote safer foods to meet domestic needs. While organic soybean is one of China’s primary organic exports, China has been the leading importer of conventional soybeans with U.S. as its largest source, but most U.S. production is transgenic. China has a labeling policy on GM (genetically modified) products, which has been more tightly enforced in recent years. This thesis examines U.S. and Chinese consumers’ valuations of attributes of processed organic products, with an emphasis on eliciting their preferences of organic ingredients from different origins, in the case of soymilk. A survey was designed for each country. The U.S. survey was administered online nationwide. An enumerated survey was administered at three types of food retail channels in Beijing, Shanghai and Guangzhou in China. Respectively, 316 and 300 responses were collected from the U.S. and China. Choice experiment was used to elicit consumer values for various attributes of soymilk in both markets. The results show that consumers in both countries are willing to pay premiums for processed foods such as soymilk with organic and non-GMO ingredients. The premium for organic soybeans is significantly higher than that for non-GMO beans. The results also indicate that U.S. consumers hold strong preferences for organic soymilk produced with domestically produced soybeans. In terms of brand preferences, U.S. respondents are willing to pay more for national brands relative to store brands, with taste as a major differentiating factor. In contrast, Chinese consumers’ valuations depend greatly on nationalities of certifying agencies. U.S. certified organic product was perceived higher than EU or Chinese certified organic products, but Chinese-certified non-GMO products were preferred over those certified by U.S. agencies. Chinese consumers’ values varied by cities and retail types where respondents were surveyed.
29
Yu, Kan Chi Kent. "Harmonic State Estimation and Transient State Estimation". Thesis, University of Canterbury. Electrical and Computer Engineering, 2006. http://hdl.handle.net/10092/1108.
Abstract (sommario):
This thesis describes the algorithms and techniques developed for harmonic state estimation and transient state estimation, which can be used to identify the location of disturbance sources in an electrical power system. The previous harmonic state estimation algorithm is extended to include the estimation of time-varying harmonics using an adaptive Kalman filter. The proposed method utilises two covariance noise models to overcome the divergence problem in traditional Kalman filters. Moreover, it does not require an optimal covariance noise matrix of the Kalman filter to be used. The common problems faced in harmonic state estimation applications due to the influence of measurement bad data associated with measurements and the lack of measurement points, hence the system being partially observable, are investigated with reference to the Lower South Island of the New Zealand system. The state estimation technique is also extended to transient state estimation. Two formulation methods are outlined and the development of the proposed methodology is presented. Fault scenarios with reference to the Lower South Island of the New Zealand system are simulated to demonstrate the ability of transient state estimation in estimating the voltages and currents of the unmeasured locations, and applying the estimated results to search for the fault location. The estimation results are compared with PSCAD/EMTDC simulations to justify their accuracy.
30
Kurdi, Ammr. "Regulation and Political Costs in the Oil and Gas Industry: An Investigation of Discretion in Reporting Earnings and Oil and Gas Reserves Estimates". Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc30481/.
Abstract (sommario):
This study investigates the use of discretion by oil and gas companies in reporting financial performance and oil and gas reserve estimates during times of high political scrutiny resulting from increases in energy prices. Hypotheses tested in prior literature state that companies facing the risk of increasing taxes or new regulations reduce reported earnings to reduce this risk. This study uses a measure of high profitability (rank order of return on assets relative to industry peers) to identify oil and gas companies more likely to manage earnings during the period from 2002 to 2008. Two measures of discretionary accruals (total and current discretionary accruals), and a measure of discretionary depreciation, depletion, and amortization (DDA) were used as indicators of discretion exercised in reporting earnings. Data on oil and gas reserve disclosures was also hand-collected from Forms 10-K to investigate whether managers use reserve estimate revisions to reduce reported earnings through increasing the annual depletion expense. Results suggest that both oil and gas refining and producing firms use negative discretionary accruals to reduce reported earnings. Results also indicate that profitability is an important determinant of the use of negative discretionary accruals by these companies regardless of the time period examined. There is also evidence that oil and gas producing firms opportunistically revise their oil and gas reserve estimates to increase depreciation, depletion, and amortization expense during periods of high oil prices.
31
Kremling, Janine. "An Analysis of the Influence of Sampling Methods on Estimation of Drug Use Prevalence and Patterns Among Arrestees in the United States: Implications for Research and Policy". Scholar Commons, 2010. http://scholarcommons.usf.edu/etd/3480.
Abstract (sommario):
Using data from the Drug Use Forecasting (DUF) and the Arrestee Drug Abuse Monitoring (ADAM) programs collected by the National Institute of Justice the question whether the drug estimates of DUF, using a non-probability sample, and the drug use estimates of ADAM, using a probability sample, yield substantially different results will be explored. The following main questions will be addressed using equivalence analysis: Are there substantial differences in the DUF and ADAM samples with regard to the drug use information obtained from arrestees at nine sites across the United States? The analysis suggests that the drug use information contained in DUF and ADAM is not substantially different for marijuana, cocaine, and opiates for all sites analyzed together. Additionally, there are no substantial differences for seven of the nine sites. The implications of these findings are discussed.
32
Fagas, Georgios. "Vibrational properties of complex solids". Thesis, Lancaster University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321898.
33
Khanal, Sami. "ESTIMATION OF ABOVEGROUND TERRESTRIAL NET PRIMARY PRODUCTIVITY AND ANALYSIS OF ITS SPATIAL AND TEMPORAL TRENDS IN THE CONTERMINOUS UNITED STATES FROM 1997 TO 2007 USING NASA CASA MODEL". MSSTATE, 2009. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07282009-150110/.
Abstract (sommario):
This study estimated monthly and annual Net Primary Productivity (NPP), an important indicator of carbon sequestration, in the Conterminous US from 1997 to 2007 using Carnegie-Ames-Stanford Approach. Vegetation condition, temperature, precipitation, photosynthetically active radiation and soil water holding capacity were used as models inputs. NPP values were lower than mean annual values during the year 2000 to 2003 which was probably due to extreme drought conditions during these years. Higher NPP per square meter was generally found in Savannah and Subtropical eco-divisions whereas Tropical/Subtropical deserts had the lowest NPP. Southeastern states had the highest NPP per square meter thus, made the highest contribution to the terrestrial carbon sequestration in US. Since the vegetation is one of the main factors in NPP and thus carbon sequestration, the results of this study could help in various environmental policy decisions on forest and cropland management at the state, EPA and federal levels.
34
Farzanehrafat, Ali. "Power Quality State Estimation". Thesis, University of Canterbury. Electrical and Computer Engineering, 2014. http://hdl.handle.net/10092/9830.
Abstract (sommario):
Traditional state estimation whereby the state of the system is assessed based on a limited number of measurements is a well established tool for steady-state situations where the frequency of the system is 50 Hz. Previous contributions have looked at extending this concept to the power quality area. This area of research is called Power Quality State Estimation (PQSE) and represents a class of techniques. Under the umbrella of PQSE, the main contribution of this work is taking Transient State Estimation (TSE) on step further. A new three-phase formulation for TSE using the Numerical Integrator Substitution (NIS) will be detailed. NIS approach, also known as Dommel's method, gives a numerical solution to describe the transient behaviour of a dynamic system at discrete time points. The new transient state estimator is implemented and verified by applying the proposed algorithm to a real distribution test system. It's performance and accuracy are investigated in presence of measurement noise, background harmonics, multiple faults, etc. The conducted study has shown this technique has a great potential.
35
Du, Toit Eben Francois. "Modelling the co-infection dynamics of HIV-1 and M. tuberculosis". Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-08172008-213855.
36
Chen, Jian. "Measurement enhancement for state estimation". [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2717.
37
Zhang, Fan. "Power system harmonic state estimation". Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/13019.
38
Sanders, Seth Robert. "State estimation in induction machines". Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/40344.
39
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.
Abstract (sommario):
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 consumption of the wood drying kiln. However,to the best of our knowledge, there is no straightforward observer design for the wood-dryingprocess in the current literature. In the first two research papers that compose this thesis, afterintroducing a state space realization of the wood drying process, a novel method for estimatingthe moisture content of the wood during drying is proposed.Compared to typical systems, observer design for nonlinear uncertain systems with timedelays, is significantly more complicated and thus attractive for research. In this thesis, theproblem of the observer design for a class of uncertain discrete-time nonlinear systems withunknown time delay has also been investigated. The study shows that by using upper and lowerbounds of the time delay, the time delay can be excluded in the observer structure. The thirdand fourth papers mostly focus on this topic based on an optimization approach.Godkänd; 2013; 20131026 (salsay); Tillkännagivande licentiatseminarium 2013-11-25 Nedanstående person kommer att hålla licentiatseminarium för avläggande av teknologie licentiatexamen. Namn: Saleh Sayyaddelshad Ämne: Reglerteknik/Automatic Control Uppsats: State Estimation of Nonlinear Systems Examinator: Professor Thomas Gustafsson, Institutionen för system- och rymdteknik, Luleå tekniska universitet Diskutant: Professor Alexander Medvedev, Avdelningen för systemteknik, Uppsala universitet Tid: Onsdag den 18 december 2013 kl 13.00 Plats: A1545, Luleå tekniska universitet
40
Ross, Linwood Matthews. "Synchrophasor's application in state estimation". Connect to this title online, 2008. http://etd.lib.clemson.edu/documents/1239896366/.
41
Chapman, Michael Addison. "Adaptation and Installation of a Robust State Estimation Package in the Eef Utility". Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/31432.
Abstract (sommario):
Robust estimation methods have been successfully applied to the problem of power system state estimation in a real-time environment. The Schweppe-type GM-estimator with the Huber psi-function (SHGM) has been fully installed in conjunction with a topology processor in the EEF utility, headquartered in Fribourg, Switzerland.
Some basic concepts of maximum likelihood estimation and robust analysis are reviewed, and applied to the development of the SHGM-estimator. The algorithms used by the topology processor and state estimator are presented, and the superior performance of the SHGM-estimator over the classic weighted least squares estimator is demonstrated on the EEF network. The measurement configuration of the EEF network has been evaluated, and suggestions for its reinforcement have been proposed.Master of Science
42
Majumdar, Ankur. "Security in power system state estimation". Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/33744.
Abstract (sommario):
With the power system evolving from passive to a more active system there is an incorporation of information and communication infrastructures in the system. The measurement data are more prone to tampering from attackers for mala fide intentions. Therefore, security and reliability of distribution have become major concerns. State estimation (SE), being the core function of the energy/distribution management system (EMS/DMS), has become necessary in order to operate the system efficiently and in a controlled manner. Although SE is a well-known task in transmission systems, it is usually not a common task in unbalanced distribution systems due to the difference in design and operation philosophy. This thesis addresses these issues and investigates the distribution system state estimation with unbalanced full three-phase modelling. The formulation, based on weighted least squares estimation, is extended to include the open/closed switches as equality constraints. This research then explores the vulnerabilities of the state estimation problem against attacks associated with leverage measurements. Detecting gross error particularly for leverage measurements have been found to be difficult due to low residuals. The thesis presents and discusses the suitability of externally studentized residuals compared to traditional residual techniques. Additionally, the masking/swamping phenomenon associated with multiple leverages makes the identification of gross error even more difficult. This thesis proposes a robust method of identifying the high leverages and then detecting gross error when the leverage measurements are compromised. All algorithms are validated in different IEEE test systems.
43
D'Arcy, Francis Gerard. "State estimation for large-scale systems". Thesis, Queen's University Belfast, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287436.
44
Nanchian, Sara. "State estimation for active distribution network". Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/58215.
Abstract (sommario):
The requirement of accommodating more distributed generations (DGs) at distribution voltage level has encouraged distribution network operators to utilize their feeder capacity more effectively. This requires the availability of the various network measurements such as voltages, currents, loads, voltage control settings and DG outputs. However these quantities are not directly available in the distribution network control centre. Therefore, to control voltage and power flow in the network, the estimations of these quantities are required. This consists of the monitoring and control of the network operation by application of modern distribution management system (DMS) at the primary substation. The state estimator takes all the available network measurement information, together with a parameterized network model and estimates state of the system in operational time scale. The estimator outputs are then fed into the main control functions and other asset management tools. Although the application of State Estimation (SE) is very common task at transmission system, the practical application are not common at distribution level. This is due to the fact that the operation, topology and design at distribution level differ from those at transmission level. The untransposed three-phase circuits, unbalanced loads, shorter lines with higher ratio of R/X, and the existence of discrete control options such as transformer tap positions illustrates some of those differences. These specificities have motivated this piece of research to consider some of the key issues in distribution system state estimation and to develop algorithms to tackle them. This thesis investigated in detail the criterion for identifying suitable solvers for the distribution system state estimation (DSSE) while considering the specific characteristic of the distribution network such as discrete tap position by exploring new optimization methods which are likely to be useful for practical implementation. Some of the research findings have already been disseminated through invited conference panel and IEEE journal.
45
Yu, Kuan-Ting Ph D. Massachusetts Institute of Technology. "Realtime state estimation for contact manipulation". Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120369.
Abstract (sommario):
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 133-140).
In this thesis, we develop a real-time state estimation system to recover the pose and contact state of an object relative to its environment. The capability to make such estimations is important for a controller to adequately react to uncertainties in a manipulation task. We propose a framework that combines tactile and visual sensing to improve the accuracy and robustness. Visual sensing is versatile and non-intrusive but suffers from occlusions and limited accuracy, especially with regard to tasks involving contact. Tactile sensing (including contact and force) is local but provides accuracy and robustness to occlusions. The framework uses online estimation techniques to fuse kinematic measurements made by a robot, contact geometry of the object and the environment, and visual measurements. In a complex contact task such as insertion, the contact formations are hard to resolve directly. We propose a data-driven method to assess the contact formation, which is then used in real time by the state estimator. We apply our framework to two iconic tasks in robotic manipulation: planar pushing and object insertion. We evaluate the algorithm in a setup instrumented to provide ground truth. The experiments show that our approach provides an accurate and robust estimation for the studied manipulation tasks.
by Kuan-Ting Yu.
Ph. D.
46
Misawa, Eduardo Akira. "Nonlinear state estimation using sliding observers". Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14549.
47
Kalmikov, Alexander G. "Uncertainty Quantification in ocean state estimation". Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79291.
Abstract (sommario):
Thesis (Ph. D.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2013.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 158-160).
Quantifying uncertainty and error bounds is a key outstanding challenge in ocean state estimation and climate research. It is particularly difficult due to the large dimensionality of this nonlinear estimation problem and the number of uncertain variables involved. The "Estimating the Circulation and Climate of the Oceans" (ECCO) consortium has developed a scalable system for dynamically consistent estimation of global time-evolving ocean state by optimal combination of ocean general circulation model (GCM) with diverse ocean observations. The estimation system is based on the "adjoint method" solution of an unconstrained least-squares optimization problem formulated with the method of Lagrange multipliers for fitting the dynamical ocean model to observations. The dynamical consistency requirement of ocean state estimation necessitates this approach over sequential data assimilation and reanalysis smoothing techniques. In addition, it is computationally advantageous because calculation and storage of large covariance matrices is not required. However, this is also a drawback of the adjoint method, which lacks a native formalism for error propagation and quantification of assimilated uncertainty. The objective of this dissertation is to resolve that limitation by developing a feasible computational methodology for uncertainty analysis in dynamically consistent state estimation, applicable to the large dimensionality of global ocean models. Hessian (second derivative-based) methodology is developed for Uncertainty Quantification (UQ) in large-scale ocean state estimation, extending the gradient-based adjoint method to employ the second order geometry information of the model-data misfit function in a high-dimensional control space. Large error covariance matrices are evaluated by inverting the Hessian matrix with the developed scalable matrix-free numerical linear algebra algorithms. Hessian-vector product and Jacobian derivative codes of the MIT general circulation model (MITgcm) are generated by means of algorithmic differentiation (AD). Computational complexity of the Hessian code is reduced by tangent linear differentiation of the adjoint code, which preserves the speedup of adjoint checkpointing schemes in the second derivative calculation. A Lanczos algorithm is applied for extracting the leading rank eigenvectors and eigenvalues of the Hessian matrix. The eigenvectors represent the constrained uncertainty patterns. The inverse eigenvalues are the corresponding uncertainties. The dimensionality of UQ calculations is reduced by eliminating the uncertainty null-space unconstrained by the supplied observations. Inverse and forward uncertainty propagation schemes are designed for assimilating observation and control variable uncertainties, and for projecting these uncertainties onto oceanographic target quantities. Two versions of these schemes are developed: one evaluates reduction of prior uncertainties, while another does not require prior assumptions. The analysis of uncertainty propagation in the ocean model is time-resolving. It captures the dynamics of uncertainty evolution and reveals transient and stationary uncertainty regimes. The system is applied to quantifying uncertainties of Antarctic Circumpolar Current (ACC) transport in a global barotropic configuration of the MITgcm. The model is constrained by synthetic observations of sea surface height and velocities. The control space consists of two-dimensional maps of initial and boundary conditions and model parameters. The size of the Hessian matrix is 0(1010) elements, which would require 0(60GB) of uncompressed storage. It is demonstrated how the choice of observations and their geographic coverage determines the reduction in uncertainties of the estimated transport. The system also yields information on how well the control fields are constrained by the observations. The effects of controls uncertainty reduction due to decrease of diagonal covariance terms are compared to dynamical coupling of controls through off-diagonal covariance terms. The correlations of controls introduced by observation uncertainty assimilation are found to dominate the reduction of uncertainty of transport. An idealized analytical model of ACC guides a detailed time-resolving understanding of uncertainty dynamics. Keywords: Adjoint model uncertainty, sensitivity, posterior error reduction, reduced rank Hessian matrix, Automatic Differentiation, ocean state estimation, barotropic model, Drake Passage transport.
by Alexander G. Kalmikov.
Ph.D.
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Graham, Matthew Corwin 1986. "Robust Bayesian state estimation and mapping". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98678.
Abstract (sommario):
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 135-146).
Virtually all robotic and autonomous systems rely on navigation and mapping algorithms (e.g. the Kalman filter or simultaneous localization and mapping (SLAM)) to determine their location in the world. Unfortunately, these algorithms are not robust to outliers and even a single faulty measurement can cause a catastrophic failure of the navigation system. This thesis proposes several novel robust navigation and SLAM algorithms that produce accurate results when outliers and faulty measurements occur. The new algorithms address the robustness problem by augmenting the standard models used by filtering and SLAM algorithms with additional latent variables that can be used to infer when outliers have occurred. Solving the augmented problems leads to algorithms that are naturally robust to outliers and are nearly as efficient as their non-robust counterparts. The first major contribution of this thesis is a novel robust filtering algorithm that can compensate for both measurement outliers and state prediction errors using a set of sparse latent variables that can be inferred using an efficient convex optimization. Next the thesis proposes a batch robust SLAM algorithm that uses the Expectation- Maximization algorithm to infer both the navigation solution and the measurement information matrices. Inferring the information matrices allows the algorithm to reduce the impact of outliers on the SLAM solution while the Expectation-Maximization procedure produces computationally efficient calculations of the information matrix estimates. While several SLAM algorithms have been proposed that are robust to loop closure errors, to date no SLAM algorithms have been developed that are robust to landmark errors. The final contribution of this thesis is the first SLAM algorithm that is robust to both loop closure and landmark errors (incremental SLAM with consistency checking (ISCC)). ISCC adds integer variables to the SLAM optimization that indicate whether each measurement should be included in the SLAM solution. ISCC then uses an incremental greedy strategy to efficiently determine which measurements should be used to compute the SLAM solution. Evaluation on standard benchmark datasets as well as visual SLAM experiments demonstrate that ISCC is robust to a large number of loop closure and landmark outliers and that it can provide significantly more accurate solutions than state-of-the-art robust SLAM algorithms when landmark errors occur.
by Matthew C. Graham.
Ph. D.
49
Runhaar, Anton Johan. "Autonomous airborne refueling : relative state estimation". Thesis, Stellenbosch : Stellenbosch University, 2011. http://hdl.handle.net/10019.1/17852.
Abstract (sommario):
Thesis (MScEng)--Stellenbosch University, 2011.ENGLISH ABSTRACT: This thesis presents the development of a state estimation system for use in an Autonomous Airborne Refueling (AAR) operation through the simulated implementation of GPS, monocular and stereoscopic vision, inertial measurement sensors and boom parameter measurement in combination with the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). A set of functional criteria for the estimation system was developed through an analysis of the control system input requirements and associated constraints. The estimation system is further developed by integrating the sensor configurations into the estimation algorithm structures through the derivation of the applicable mathematical models. Final sensor configurations are set based on a sensitivity analysis in which the effect of parameters such as sensor noise, placement and quantity are related to the accuracy with which the states are estimated. Uncertainty in the process noise, which is typically approximated, is overcome by adding an adaptive element to the estimation algorithms in which the current process noise is estimated allowing compensation for unmodeled process noise uncertainty. Finally twelve practical sensor configurations are established utilising unique combinations of the five sensors. Each configuration is simulated using both estimation algorithms after which all results are evaluated with respect to one another as well as to the minimum state accuracy criteria. Conclusions are presented based on the evaluation of the results followed by recommendation for future development.
AFRIKAANSE OPSOMMINGS: Die ontwikkeling van ’n toestandafskattingstelsel, spesifiek toegepas op outonome brandstofhervulling, word voorgelê in hierdie tesis. Hierdie ontwikkeling behels die implementering van GPS, monukulêre- en stereo-visie sensors, inersiële sensor eenhede en verbindingsarmsensors wat gebruik word in ’n Uitgebruide Kalman Filter (Extended Kalman Filter) en Geurlose Kalman Filter (Unscented Kalman Filter). ’n Volledige ontleding van die beheerstelsel se toevoervereistes en geassosieerde beperkings is gebruik om ’n stel beoordelingsmaatstawwe vir die toestandafskatting-stelsel te bepaal. Die stelsel is verder ontwikkel deur verskillende sensorkonfigurasies met die afskattingsalgoritmes te kombineer deur die afleiding van toepaslike wiskundinge modelle. Hierdie konfigurasies is verfyn deur ’n sensitiwiteitsanalise, waar die verwantskap tussen die effekte van sensorruis, sensorligging, hoeveelheid sensors ondersoek is met betrekking tot afskattingsakkuraatheid. Onsekerheid in die stelsel se prosesruis is deur ’n aanpassings substelsel hanteer, wat kompensasie vir ongemodeleerde onsekerheid moontlik maak. Twaalf praktiese sensorkonfigurasies is opgestel vanuit unieke kombinasies van die vyf sensore behartig in die projek. Hierdie konfigurasies is deur beide afskattingsalgoritmes gebruik om sodoende die akkuraatheid van die konfigurasies asook die afskattingsalgoritmes te evalueer met betrekking tot mekaar en aan die hand van die beoordelingsmaatstawwe vir die beheerstelsel. Die tesis is afgesluit deur gevolgtrekkings asook aanbevelings vir toekomstige navorsing.
50
Phaniraj, Viruru. "Robust state estimation in power systems". Diss., Virginia Tech, 1991. http://hdl.handle.net/10919/39776.