A class of immersed finite element (IFE) spaces is developed for solving elliptic boundary value problems that have interfaces. IFE spaces are finite element approximation spaces which are based upon meshes that can be independent of interfaces in the domain. Three different quadratic IFE spaces and their related biquadratic IFE spaces are introduced here for the purposes of solving both forward and inverse elliptic interface problems in 1D and 2D. These different spaces are constructed by (i) using a hierarchical approach, (ii) imposing extra continuity requirements or (iii) using a local refinement technique. The interpolation properties of each space are tested against appropriate testing functions in 1D and 2D. The IFE spaces are also used to approximate the solution of a forward elliptic interface problem using the Galerkin finite element method and the mixed least squares finite element method. Finally, one appropriate space is selected to solve an inverse interface problem using either an output least squares approach or the least squares with mixed equation error method. / Ph. D.

In this thesis, we consider a projection-based stabilization method for solving buoyancy driven flows (natural convection problems). The method consists of adding global stabilization for all scales and then anti-diffusing these effects on the large scales defined by projections into appropriate function spaces. In this way, stabilization acts only on the small scales. We consider two different variations of buoyancy driven flows based on the projection-based stabilization. First, we focus on the steady-state natural convection problem of heat transport through combined solid and fluid media in a classical enclosure. We present the mathematical analysis of the projection-based method and prove existence, uniqueness and convergence of the approximate solutions of the velocity, temperature and pressure. We also present some numerical tests to support theoretical findings. Second, we consider a system of combined heat and mass transfer in a porous medium due to the natural convection. For the semi-discrete problem, a stability analysis of the projectionbased method and a priori error estimate are given for the Darcy-Brinkman equations in double-diffusive convection. Then we provide numerical assessments and a comparison with some benchmark data for the Darcy-Brinkman equations. In the last part of the thesis, we present a fully discrete scheme with the linear extrapolation of convecting velocity terms for the Darcy-Brinkman equations.

Adaptive filtering techniques are used in a wide range of applications, including echo cancellation, adaptive equalization, adaptive noise cancellation, and adaptive beamforming. The performance of an adaptive filtering algorithm is evaluated based on its convergence rate, misadjustment, computational requirements, and numerical robustness. We attempt to improve the performance by developing new adaptation algorithms and by using "unconventional" structures for adaptive filters. Part I of this dissertation presents a new adaptation algorithm, which we have termed the Normalized LMS algorithm with Orthogonal Correction Factors (NLMS-OCF). The NLMS-OCF algorithm updates the adaptive filter coefficients (weights) on the basis of multiple input signal vectors, while NLMS updates the weights on the basis of a single input vector. The well-known Affine Projection Algorithm (APA) is a special case of our NLMS-OCF algorithm. We derive convergence and tracking properties of NLMS-OCF using a simple model for the input vector. Our analysis shows that the convergence rate of NLMS-OCF (and also APA) is exponential and that it improves with an increase in the number of input signal vectors used for adaptation. While we show that, in theory, the misadjustment of the APA class is independent of the number of vectors used for adaptation, simulation results show a weak dependence. For white input the mean squared error drops by 20 dB in about 5N/(M+1) iterations, where N is the number of taps in the adaptive filter and (M+1) is the number of vectors used for adaptation. The dependence of the steady-state error and of the tracking properties on the three user-selectable parameters, namely step size, number of vectors used for adaptation (M+1), and input vector delay D used for adaptation, is discussed. While the lag error depends on all of the above parameters, the fluctuation error depends only on step size. Increasing D results in a linear increase in the lag error and hence the total steady-state mean-squared error. The optimum choices for step size and M are derived. Simulation results are provided to corroborate our analytical results. We also derive a fast version of our NLMS-OCF algorithm that has a complexity of O(NM). The fast version of the algorithm performs orthogonalization using a forward-backward prediction lattice. We demonstrate the advantages of using NLMS-OCF in a practical application, namely stereophonic acoustic echo cancellation. We find that NLMS-OCF can provide faster convergence, as well as better echo rejection, than the widely used APA. While the first part of this dissertation attempts to improve adaptive filter performance by refining the adaptation algorithm, the second part of this work looks at improving the convergence rate by using different structures. From an abstract viewpoint, the parameterization we decide to use has no special significance, other than serving as a vehicle to arrive at a good input-output description of the system. However, from a practical viewpoint, the parameterization decides how easy it is to numerically minimize the cost function that the adaptive filter is attempting to minimize. A balanced realization is known to minimize the parameter sensitivity as well as the condition number for Grammians. Furthermore, a balanced realization is useful in model order reduction. These properties of the balanced realization make it an attractive candidate as a structure for adaptive filtering. We propose an adaptive filtering algorithm based on balanced realizations. The third part of this dissertation proposes a unit-norm-constrained equation-error based adaptive IIR filtering algorithm. Minimizing the equation error subject to the unit-norm constraint yields an unbiased estimate for the parameters of a system, if the measurement noise is white. The proposed algorithm uses the hyper-spherical transformation to convert this constrained optimization problem into an unconstrained optimization problem. It is shown that the hyper-spherical transformation does not introduce any new minima in the equation error surface. Hence, simple gradient-based algorithms converge to the global minimum. Simulation results indicate that the proposed algorithm provides an unbiased estimate of the system parameters. / Ph. D.

Aircraft system identification has been widely used to this day in applications like control law design, building simulators or extending flight envelopes. It can also be utilized for determining flight-mechanical characteristics in the preliminary design phase of a flight vehicle. In this thesis, three common time-domain methods were implemented in MATLAB for determining the aerodynamic derivatives of a subscale aircraft. For parameter estimation, the equation-error method is quick, robust and can provide good parameter estimates on its own. The output-error method is computationally intensive but keeps account of the aircraft's evolution in time, being more suitable for fine-tuning predictive models. A new model structure is identified using multivariate orthogonal functions with a predicted squared error stopping criteria. This method is based on linear regression (equation-error). The code written is flexible and can also be used for other aircraft and with other aerodynamic models. Simulations are compared with experimental data from a previous flight test campaign for validation. In the future, this tool may help taking decisions in conceptual design after a prototype is tested.

This doctoral study aims to develop a methodology for use in determining aerodynamic models and parameters from actual flight test data for different types of autonomous flight vehicles. The stepwise regression method and equation error method are utilized for the aerodynamic model identification and parameter estimation. A closed loop aerodynamic parameter estimation approach is also applied in this study which can be used to fine tune the model parameters. Genetic algorithm is used as the optimization kernel for this purpose. In the optimization scheme, an input error cost function is used together with a final position penalty as opposed to widely utilized output error cost function. Available methods in the literature are developed for and mostly applied to the aerodynamic system identification problem of piloted aircraft / a very limited number of studies on autonomous vehicles are available in the open literature. This doctoral study shows the applicability of the existing methods to aerodynamic model identification and parameter estimation problem of autonomous vehicles. Also practical considerations for the application of model structure determination methods to autonomous vehicles are not well defined in the literature and this study serves as a guide to these considerations.

Le travail de recherche présenté dans ce mémoire est une contribution à l'estimation des modèles Linéaires à Paramètres Variants (LPV) à temps continu. Dans un premier temps, il traite de façon originale la modélisation quasi-LPV des échangeurs de chaleur pour la détection d'encrassement durant les régimes transitoires. La méthodologie définie dans cette thèse est introduite pas à pas pour caractériser un échangeur à courants croisés puis pour celle d'un échangeur à contre-courants montrant ainsi la généricité de l'approche pour la modélisation des échangeurs thermiques. Une méthode locale basée sur une estimation initiale de modèles LTI en différents points du domaine de fonctionnement est utilisée pour construire le modèle LPV en agrégeant les paramètres des différents modèles locaux grâce à une méthode d'interpolation polynomiale liée aux débits massiques. Le modèle quasi-LPV de l'échangeur élaboré en fonctionnement sain permet ainsi d'envisager la détection de l'encrassement dans les échangeurs de chaleur en comparant ses sorties à ceux provenant du procédé. Dans un second temps, ce travail porte sur l'identification des systèmes LPV à représentation entrée-sortie à temps continu par une approche globale. Une solution pratique pour l'identification directe de tels systèmes est proposée. Elle est basée sur l'utilisation d'un algorithme à erreur de sortie initialisé par une approche à erreur d'équation, la méthode des Moments Partiels Réinitialisés. Des simulations illustrent les performances de l'approche proposée. / The research work presented in this thesis is a contribution to the estimation of Linear Parameter Varying (LPV) models in continuous-time. First, a quasi-LPV modeling of heat exchangers is tackled in an original way. This quasi-LPV model is meant to be used for fouling detection (during transient phases). A step-by-step description of the methodology is given on how to model a cross flow heat exchanger. Applying the same approach on a counter flow shows its genericity in the heat exchanger field. A local method, based on an estimation of LTI models for different operating points, is used to build the LPV model by interpolation of the various LTI model parameters. The resulting quasi-LPV model for a clean heat exchanger can thus be used for fouling detection by comparison of real and model outputs for the same input signals. Secondly, this work concerns the identification of continuous-time input-output LPV systems through a global approach. A practical solution for the direct identification of such systems is proposed. It is based on the use of an output-error algorithm initialized by an equation error based approach, the reinitialized partial moment's method. Simulations illustrate the performance of the proposed approach.

Tato práce je zaměřena na odhad letových parametrů malého letounu, konkrétně letounu Evektor SportStar RTC. Pro odhad letových parametrů jsou použity metody "Equation Error Method", "Output Error Method" a metody rekurzivních nejmenších čtverců. Práce je zaměřena na zkoumání charakteristik aerodynamických parametrů podélného pohybu a ověření, zda takto odhadnuté letové parametry odpovídají naměřeným datům a tudíž vytvářejí předpoklad pro realizaci dostatečně přesného modelu letadla. Odhadnuté letové parametry jsou dále porovnávány s a-priorními hodnotami získanými s využitím programů Tornado, AVL a softwarovéverze sbírky Datcom. Rozdíly mezi a-priorními hodnotami a odhadnutými letovými paramatery jsou porovnány s korekcemi publikovanými pro subsonické letové podmínky modelu letounu F-18 Hornet.