Simultaneous evaluation of the whole set of the model parameters of different orders together with an ability to track unmodeled dynamics are desired features in the tasks of parameter estimation. A technique handling with the factors produced by an augmented covariance (ACM) or information (AIM) matrices is considered to be an appropriate tool for designing multiple model estimation. This is where the name augmented identification (AI) by using the least-squares method was taken. The method AI attains numerical stability of the calculation of the conventional least squares method while in the same time, fully extracts information contained in the observation. In order to track time varying parameters can be found that all the information pertinent to recursive identification and thus to data driven forgetting is concentrated in ACM as well as in AIM. In this thesis will be introduced how to selective forgetting to ACM should be applied in an effective way. It means forget only a portion of accumulated information which will be further modified by the newest data included in the regressor. In the estimation problems the knowledge of the inner states of the identified system is often required. Because the augmented identification belongs within the class so called prediction error method (PEM), some rational requirements can be deduced. As a result, state filter should constitute optimization procedure minimizing the predicted error of given state space model representation with respect to the vector of states. The proposed scheme will considerably extend the family of algorithms based on processing of ACM (AIM) about augmented filtering (AF). This all will establish a comprehensive concept of parametric estimation that compared with conventional approaches is characterized by versatility, low demands on a priori process information and by excellent numerical properties (robust against overparametrization, capable solving the multiple model problem).

Tato práce se zabývá návrhem adaptivního řídícího algortitmu pro konkrétní třídu elektromechanických aktuátorů, založeného na principu dopředného řízení pomocí inverzního dynamického modelu. Adaptibilita řízení spočívá v mechanismu získání inverzního dynamického modelu. Tato práce se zaměřuje na jeho online aproximaci pomocí lokálních aproximačních metod. Výstupem práce je shrnutí analýzy, simulačního testování a reálných experimentů, které testovaly možnosti praktického využití lokálných aproximačních metod pro účely adaptivního řízení v reálném prostředí.

In this paper we deal with the `strength' of ill-posedness for ill-posed linear operator equations Ax = y in Hilbert spaces, where we distinguish according_to_M. Z. Nashed [15] the ill-posedness of type I if A is not compact, but we have R(A) 6= R(A) for the range R(A) of A; and the ill-posedness of type II for compact operators A: From our considerations it seems to follow that the problems with noncompact operators A are not in general `less' ill-posed than the problems with compact operators. We motivate this statement by comparing the approximation and stability behaviour of discrete least-squares solutions and the growth rate of Galerkin matrices in both cases. Ill-posedness measures for compact operators A as discussed in [10] are derived from the decay rate of the nonincreasing sequence of singular values of A. Since singular values do not exist for noncompact operators A; we introduce stability rates in order to have a common measure for the compact and noncompact cases. Properties of these rates are illustrated by means of convolution equations in the compact case and by means of equations with multiplication operators in the noncompact case. Moreover using increasing rearrangements of the multiplier functions specific measures of ill-posedness called ill-posedness rates are considered for the multiplication operators. In this context, the character of sufficient conditions providing convergence rates of Tikhonov regularization are compared for compact operators and multiplication operators.

<p>Real-time hybrid simulation (RTHS) has demonstrated certain advantages over conventional large-scale testing. In an RTHS, the system that is under study is partitioned into a numerical and a physical substructure, where the numerical part is comprised of those elements that are easier to model mathematically, while the physical part consists of those that present a complex behavior difficult to capture in a numerical model. The most complex part of this study is the isolation system, a technology used to protect structures against earthquakes by modifying how they respond to ground motions. Unbonded Fiber Reinforced Elastomeric Isolators (UFREIs) are devices that can accomplish this task and have gained attention in recent years because of their modest but valuable features that make them suitable for implementation in low-rise buildings and in developing countries because of their low cost. Our end goal for this work is to enable the testing of scaled versions of these elastomeric isolators to understand their behavior under shear tests and realistic loading. </p> <p>A testing instrument was designed and constructed to apply a uniaxial compressive force up to 22kN and a shear force of 8kN simultaneously to the specimens. A testing program was conducted where four primary sources of signal distortion were identified as caused by the servo-hydraulic system. From these results, a mechanics-based model was developed to understand better the dynamics that the sliding table can introduce to the measured signals accounting for inertial and dissipative forces. Two Bouc-Wen models were implemented to simulate the behavior of the UFREIs. The first only accounts for the hysteretic behavior of the isolator, and the second accounts for the additional nonlinearities found in the isolator’s behavior. These models were assembled in a virtual RTHS which is available to users interested in learning the applications of RTHS of a base-isolated structure with a nonlinear component.</p> <p>An RTHS experiment was conducted in the IISL where the control system comprised a delay compensator and a proportional-integral controller, which exhibited a good tracking performance with minimal delay and low RMSE. However, it can increase the distortion of the oil-column resonance in the measured signals. The simulation captures the behavior of the isolated structure for small displacements. However, it underestimates the displacement of the full-scale specimen for large displacements. The RTHS showed a better approximation of the displacement of the full-scale structure than the theoretical behavior approximated by the Bouc-Wen models.</p>

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近年來由於溫室效應加劇以及氣候變遷加劇，因此符合綠色運輸特性的公共自行車系統，成為各國交通部門發展綠運輸政策時的目標之一，同時，大數據分析亦是目前受到高度關注的熱門議題。而本研究首先使用臺北市微笑單車租借大數據探討在不同時間點下民眾日常使用微笑單車之旅運行為，分析不同站點間的旅次特性。再運用社群網絡分析，以站點之間旅次連結多寡作為權重，探討站點間之緊密程度，以及不同時間點下微笑單車租借量之熱點分布情形，並將其視覺化呈現。 後續透過文獻分析，擷取影響公共自行車使用量之因素後，本研究嘗試運用一般線性迴歸模型與地理加權迴歸進行模型建立，並探討各影響因素對於旅運需求之影響情形。實證結果顯示，地理加權迴歸模型可以解決一般線性迴歸所產生空間自相關問題，使得模型解釋能力獲得改善。本研究並使用地理加權迴歸進行使用需求分析以及預測，對未來公共自行車營運以及站點擴張提出結論以及建議，期能提升公共自行車系統之使用量。 / Due to the climate change and aggravation of the greenhouse effect in recent years, the public bicycle system with the feature of low-carbon emission has raised more and more attention internationally, and has become one of the targets in developing green transportation policies of transportation departments of governments around the world. Meanwhile Big Data analysis issues, on the other hand, are currently a sought-after topic which has caused great concern as well. In this study, we utilize the rental data of the YouBike system in Taipei to discuss the public usage of YouBike tour at different periods. With the use of social network analysis, we discuss the relationships between different bicycle stops based on applying the number of travels between different sites as the weight. Eventually, the hotspot analysis will be carried out by operating the GIS system. In this way, we are able to discuss the hotspot distribution of YouBike rentals in different time and then visualize the result. After that this study pick up the variables which will effect the YouBike usage by reference review. This research try to built models by utilizing the Least Squares Method and Geographically Weighted Regression. Then we will have a discussion with the result of the two models. The result shows that Geographically Weighted Regression can resolve the spatial autocorrelation problem which happened in the Least Squares Method and to gain a better result. With the analysis and prediction of public bicycle system from Geographically Weighted Regression, we hope to raise the usage of public bicycle system by concluding as well as making recommendations for the future operation of public bicycle and the expansion of bicycle stops.

The doctoral thesis deals with the valuer issues of business valuation with construction production in the condition of the Czech economy. The business valuation issue is, and will always be, highly relevant in a market economy environment, with regard to both methodical and practical approaches. The main aim of the doctoral thesis is to demonstrate the dependence constructing empirical regression model to determine the value of the construction enterprise by the chosen income valuation method based on the equity (book value of equity in historical costs). The first part of the doctoral thesis is a research study describing the approach of the authors to the current state of knowledge concerning the issues of business valuation, aspects of equity, using the principles of system methodology. Based on these findings, a space is defined in which it is possible to propose a solution of a partial problem in terms of selecting the enterprise value category and the associated income valuation methods suitable for extensive time-series analysis. An integral part of the doctoral thesis is the determination of the sample size of construction enterprises according to the assumptions and limitations of the chosen methodology. Empirical research for data collection is based on Justice.cz database. Another important part is, in the spirit of system approach principles, the choice and application of the method of system discipline for the solved problem of doctoral thesis. The result of the solution is an empirical regression model, which after subsequent validation in multiple case studies could also be recommended for wider verification in valuers practice. Part of the thesis will also include discussions in the wider context of the potential benefits of the doctoral thesis for practical, theoretical and pedagogical use.

This thesis is concerned with problems of measuring and mapping of magnetic field in MR tomograph, for purpose of magnetic flux density homogeneity optimization. Attention is paid to mapping techniques on rotary symmetric volume and to ways of magnetic fields optimization with utilization of passive and active correction systems. Theoretical analysis of magnetic field decomposition with utilization of spherical harmonics and numerical decomposition is made. Mapping and approximation techniques of basic magnetic field are verified by experiments in the laboratory at the Institute of Scientific Instruments AS CR in Brno.

Traverses Adjustment in the surface of the ellipsoid with the objectives to guarantee the solution unicity in the transport of curvilinear geodesic coordinates (latitude and longitude) and in the azimuth transport and to get the estimates of quality. It deduces the coordinate transport and the azimuth transport by mean Legendre s series of the geodesic line. This series is based on the Taylor s series, where the argument is the length of the geodesic line. For the practical applications, it has the necessity to effect the truncation of the series and to calculate the function error for the latitude, the function error for the longitude and the function error for the azimuth. In this research, these series are truncated in the derivative third and calculates the express functions error in derivative fourth. It is described the adjustment models based on the least-squares method: combined model with weighted parameters, combined model or mixed model, parametric model or observations equations and correlates model or condition equations model. The practical application is the adjustment by mean parametric model of a traverse measured by the Instituto Brasileiro de Geografia e Estatística (IBGE), constituted of 8 vertices and the 129.661 km length. The localization of errors in the observations is calculated by the Baarda s data snooping test in the last iteration of the adjustment that showed some observations with error. The estimates of quality are in the variance-covariance matrices and calculate the semiaxes of the error ellipse or standard ellipse of each point by means of the spectral decomposition (or Jordan s decomposition) of the submatrices of the variance-covariance matrix of the adjusted parameters (the coordinates). It is important to note that the application of the Legendre s series is satisfactory for short distances until 40km length. The convergence of the series is fast for the adjusted coordinates, where the stopped criterion of the iterations is four decimals in the sexagesimal second arc, where it is obtained from interation second of the adjustment. / Ajustamento de linhas poligonais na superfície do elipsóide com os objetivos de garantir a unicidade de solução no transporte de coordenadas geodésicas curvilíneas (latitude ϕ e longitude λ ) e no transporte de azimute e de obter as estimativas de qualidade. Deduz o transporte de coordenadas e o transporte de azimute pelas séries de Legendre da linha geodésica. Essa série se fundamenta na série de Taylor, em que o argumento é o comprimento da linha geodésica. Para as aplicações práticas, há a necessidade de efetuar o truncamento da série e calcular a função erro para a latitude, função erro para a longitude e função erro para o azimute. Nesta pesquisa, trunca-se a série na derivada terceira e calculam-se as funções erro expressas em derivada quarta. Expõe os modelos de ajustamento fundamentados no método dos mínimos quadrados (MMQ): modelo combinado com ponderação aos parâmetros, modelo combinado ou implícito, modelo paramétrico ou das equações de observação e modelo dos correlatos ou das equações de condição. A aplicação prática é o ajustamento pelo modelo paramétrico de uma linha poligonal medida pelo Instituto Brasileiro de Geografia e Estatística (IBGE), constituída de 8 vértices e de comprimento igual a 129,661 km. A localização de erros nas observações é efetuada pelo teste data snooping de Baarda na última etapa do ajustamento que mostrou algumas observações com erro. As estimativas de qualidade estão nas matrizes variância-covariância (MVC) e calcula-se os semieixos da elipse dos erros (ou elipse padrão) de cada ponto mediante a decomposição espectral (ou decomposição de Jordan) das submatrizes da MVC dos parâmetros (as coordenadas) ajustados. Mostra-se que a aplicação das séries de Legendre é satisfatória para distâncias curtas até 40km. A convergência da série é rápida para as coordenadas ajustadas, onde o critério de parada das iterações seja quatro decimais do segundo de arco em que se atingiu na segunda etapa do ajustamento.

Aim of this thesis is building of a simulator model of a rotary (Furuta) pendulum and design of appropriate regulators. This paper describes assembly of a nonlinear simulator model, using Matlab–Simulink and its library Simscape–Simmechanics. Furthermore the paper discuss linear discrete model obtained from the system response, using least squares method. This linear model serves as aproximation of the system for designing of two linear discrete state space regulators with sumator. These regulators are supported by a simple swing–up regulator and logics managing cooperation.