Dissertations / Theses on the topic 'Recursive Least Squares'
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Baykal, Buyurman. "Underdetermined recursive least-squares adaptive filtering." Thesis, Imperial College London, 1995. http://hdl.handle.net/10044/1/7790.
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Bian, Xiaomeng. "Completely Recursive Least Squares and Its Applications." ScholarWorks@UNO, 2012. http://scholarworks.uno.edu/td/1518.
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The matrix-inversion-lemma based recursive least squares (RLS) approach is of a recursive form and free of matrix inversion, and has excellent performance regarding computation and memory in solving the classic least-squares (LS) problem. It is important to generalize RLS for generalized LS (GLS) problem. It is also of value to develop an efficient initialization for any RLS algorithm.
In Chapter 2, we develop a unified RLS procedure to solve the unconstrained/linear-equality (LE) constrained GLS. We also show that the LE constraint is in essence a set of special error-free observations and further consider the GLS with implicit LE constraint in observations (ILE-constrained GLS).
Chapter 3 treats the RLS initialization-related issues, including rank check, a convenient method to compute the involved matrix inverse/pseudoinverse, and resolution of underdetermined systems. Based on auxiliary-observations, the RLS recursion can start from the first real observation and possible LE constraints are also imposed recursively. The rank of the system is checked implicitly. If the rank is deficient, a set of refined non-redundant observations is determined alternatively.
In Chapter 4, base on [Li07], we show that the linear minimum mean square error (LMMSE) estimator, as well as the optimal Kalman filter (KF) considering various correlations, can be calculated from solving an equivalent GLS using the unified RLS.
In Chapters 5 & 6, an approach of joint state-and-parameter estimation (JSPE) in power system monitored by synchrophasors is adopted, where the original nonlinear parameter problem is reformulated as two loosely-coupled linear subproblems: state tracking and parameter tracking. Chapter 5 deals with the state tracking which determines the voltages in JSPE, where dynamic behavior of voltages under possible abrupt changes is studied. Chapter 6 focuses on the subproblem of parameter tracking in JSPE, where a new prediction model for parameters with moving means is introduced. Adaptive filters are developed for the above two subproblems, respectively, and both filters are based on the optimal KF accounting for various correlations. Simulations indicate that the proposed approach yields accurate parameter estimates and improves the accuracy of the state estimation, compared with existing methods.
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Hutchinson, Derek Charles Glenn. "Manipulator inverse kinematics based on recursive least squares estimation." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27890.
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The inverse kinematics problem for six degree of freedom robots having a separable structure with the wrist equivalent to a spherical joint is considered and an iterative solution based on estimating the inverse Jacobian by recursive least squares estimation is proposed. This solution is found to have properties similar to Wampler's Damped Least Squares method and provides a stable result when the manipulator is in singular regions. Furthermore, the solution is more computationally efficient than Wampler's method; however, its best performance is obtained when the distances between the current end effector pose and the target pose are small. No knowledge of the manipulator's geometry is required provided that the end effector and joint position data are obtained from sensor information. This permits the algorithm to be readily transferable among manipulators and circumvents detailed analysis of the manipulator's structure.Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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Walke, Richard Lewis. "High sample-rate Givens rotations for recursive least squares." Thesis, University of Warwick, 1997. http://wrap.warwick.ac.uk/36283/.
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The design of an application-specific integrated circuit of a parallel array processor is considered for recursive least squares by QR decomposition using Givens rotations, applicable in adaptive filtering and beamforming applications. Emphasis is on high sample-rate operation, which, for this recursive algorithm, means that the time to perform arithmetic operations is critical. The algorithm, architecture and arithmetic are considered in a single integrated design procedure to achieve optimum results. A realisation approach using standard arithmetic operators, add, multiply and divide is adopted. The design of high-throughput operators with low delay is addressed for fixed- and floating-point number formats, and the application of redundant arithmetic considered. New redundant multiplier architectures are presented enabling reductions in area of up to 25%, whilst maintaining low delay. A technique is presented enabling the use of a conventional tree multiplier in recursive applications, allowing savings in area and delay. Two new divider architectures are presented showing benefits compared with the radix-2 modified SRT algorithm. Givens rotation algorithms are examined to determine their suitability for VLSI implementation. A novel algorithm, based on the Squared Givens Rotation (SGR) algorithm, is developed enabling the sample-rate to be increased by a factor of approximately 6 and offering area reductions up to a factor of 2 over previous approaches. An estimated sample-rate of 136 MHz could be achieved using a standard cell approach and O.35pm CMOS technology. The enhanced SGR algorithm has been compared with a CORDIC approach and shown to benefit by a factor of 3 in area and over 11 in sample-rate. When compared with a recent implementation on a parallel array of general purpose (GP) DSP chips, it is estimated that a single application specific chip could offer up to 1,500 times the computation obtained from a single OP DSP chip.
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Tsakiris, Manolis. "On the regularization of the recursive least squares algorithm." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-21102010-101424/.
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This thesis is concerned with the issue of the regularization of the Recursive Least-Squares (RLS) algorithm. In the first part of the thesis, a novel regularized exponentially weighted array RLS algorithm is developed, which circumvents the problem of fading regularization that is inherent to the standard regularized exponentially weighted RLS formulation, while allowing the employment of generic time-varying regularization matrices. The standard equations are directly perturbed via a chosen regularization matrix; then the resulting recursions are extended to the array form. The price paid is an increase in computational complexity, which becomes cubic. The superiority of the algorithm with respect to alternative algorithms is demonstrated via simulations in the context of adaptive beamforming, in which low filter orders are employed, so that complexity is not an issue. In the second part of the thesis, an alternative criterion is motivated and proposed for the dynamical regulation of regularization in the context of the standard RLS algorithm. The regularization is implicitely achieved via dithering of the input signal. The proposed criterion is of general applicability and aims at achieving a balance between the accuracy of the numerical solution of a perturbed linear system of equations and its distance from the analytical solution of the original system, for a given computational precision. Simulations show that the proposed criterion can be effectively used for the compensation of large condition numbers, small finite precisions and unecessary large values of the regularization.Esta tese trata da regularização do algoritmo dos mínimos-quadrados recursivo (Recursive Least-Squares - RLS). Na primeira parte do trabalho, um novo algoritmo array com matriz de regularização genérica e com ponderação dos dados exponencialmente decrescente no tempo é apresentado. O algoritmo é regularizado via perturbação direta da inversa da matriz de auto-correlação (Pi) por uma matriz genérica. Posteriormente, as equações recursivas são colocadas na forma array através de transformações unitárias. O preço a ser pago é o aumento na complexidade computacional, que passa a ser de ordem cúbica. A robustez do algoritmo resultante ´e demonstrada via simula¸coes quando comparado com algoritmos alternativos existentes na literatura no contexto de beamforming adaptativo, no qual geralmente filtros com ordem pequena sao empregados, e complexidade computacional deixa de ser fator relevante. Na segunda parte do trabalho, um critério alternativo ´e motivado e proposto para ajuste dinâmico da regularização do algoritmo RLS convencional. A regularização é implementada pela adição de ruído branco no sinal de entrada (dithering), cuja variância é controlada por um algoritmo simples que explora o critério proposto. O novo critério pode ser aplicado a diversas situações; procura-se alcançar um balanço entre a precisão numérica da solução de um sistema linear de equações perturbado e sua distância da solução do sistema original não-perturbado, para uma dada precisão. As simulações mostram que tal critério pode ser efetivamente empregado para compensação de números de condicionamento (CN) elevados, baixa precisão numérica, bem como valores de regularização excessivamente elevados.
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Lightbody, Gaye. "High performance VLSI architectures for recursive least squares adaptive filtering." Thesis, Queen's University Belfast, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313974.
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Thompson, Kenneth. "Position estimation in a switched reluctance motor using recursive least squares." Thesis, University of Newcastle Upon Tyne, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366575.
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Lauzon, Anne-Marie. "The time course of bronchoconstriction and its assessment by recursive least-squares." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=41672.
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A recursive least-squares algorithm was developed to estimate respiratory mechanical parameters with high temporal resolution. This algorithm was used to investigate the time course of bronchoconstriction induced by intravenous histamine injection in the dog. The onset of the response of lung tissue resistance and elastance demonstrated a different time course than airway resistance. This was interpreted in terms of the sequential delivery of the drug first through the pulmonary and then the bronchial circulations. The time course of respiratory mechanical parameters among various alveolar capsules revealed two patterns of inhomogeneity development. The first one was random whereas the second one was progressive with dose. A mathematical derivation elucidated the negative tissue resistance frequently obtained at high levels of constriction. The time courses of respiratory resistance and elastance during bronchoconstriction were transient and scaled with dose. They were reproducible for repeated doses of histamine after indomethacin pre-treatment and were intrinsically modulated by the adrenergic sympathetic system and through the $ rm H sb2$ histamine receptors.
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Huo, Jia Q. "Numerical properties of adaptive recursive least-squares (RLS) algorithms with linear constraints." Thesis, Curtin University, 1999. http://hdl.handle.net/20.500.11937/270.
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Adaptive filters have found applications in many signal processing problems. In some situations, linear constraints are imposed on the filter weights such that the filter is forced to exhibit a certain desired response. Several algorithms for linearly constrained least-squares adaptive filtering have been developed in the literature. When implemented with finite precision arithmetic, these algorithms are inevitably subjected to rounding errors. It is essential to understand how these algorithms react to rounding errors.In this thesis, the numerical properties of three linearly constrained least-squares adaptive filtering algorithms, namely, the linearly constrained fast least algorithm, the linear systolic array for MVDR beamforming and the linearly constrained QRD-RLS algorithm, are studied. It is shown that all these algorithms can be separated into a constrained part and an unconstrained part. The numerical properties of unconstrained least-squares algorithms (i.e., the unconstrained part of the linearly constrained algorithms under study) are reviewed from the perspectives of error propagation, error accumulation and numerical persistency. It is shown that persistent excitation and sufficient numerical resolution are needed to ensure the stability of the CRLS algorithm, while the QRD-RLS algorithm is unconditionally stable. The numerical properties of the constrained algorithms are then examined. Based on the technique of how the constraints are applied, these algorithms can be grouped into two categories. The first two algorithms admit a similar structure in that the unconstrained parts preceed the constrained parts. Error propagation analysis shows that this structure gives rise to unstable error propagation in the constrained part. In contrast, the constrained part of the third algorithm preceeds the unconstrained part. It is shown that this algorithm gives an exact solution to a linearly constrained least-squares adaptive filtering problem with perturbed constraints and perturbed input data. A minor modification to the constrained part of the linearly constrained QRD-RLS algorithm is proposed to avoid a potential numerical difficulty due to the Gaussian elimination operation employed in the algorithm.
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Huo, Jia Q. "Numerical properties of adaptive recursive least-squares (RLS) algorithms with linear constraints." Curtin University of Technology, Australian Telecommunications Research Institute, 1999. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=10094.
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Adaptive filters have found applications in many signal processing problems. In some situations, linear constraints are imposed on the filter weights such that the filter is forced to exhibit a certain desired response. Several algorithms for linearly constrained least-squares adaptive filtering have been developed in the literature. When implemented with finite precision arithmetic, these algorithms are inevitably subjected to rounding errors. It is essential to understand how these algorithms react to rounding errors.In this thesis, the numerical properties of three linearly constrained least-squares adaptive filtering algorithms, namely, the linearly constrained fast least algorithm, the linear systolic array for MVDR beamforming and the linearly constrained QRD-RLS algorithm, are studied. It is shown that all these algorithms can be separated into a constrained part and an unconstrained part. The numerical properties of unconstrained least-squares algorithms (i.e., the unconstrained part of the linearly constrained algorithms under study) are reviewed from the perspectives of error propagation, error accumulation and numerical persistency. It is shown that persistent excitation and sufficient numerical resolution are needed to ensure the stability of the CRLS algorithm, while the QRD-RLS algorithm is unconditionally stable. The numerical properties of the constrained algorithms are then examined. Based on the technique of how the constraints are applied, these algorithms can be grouped into two categories. The first two algorithms admit a similar structure in that the unconstrained parts preceed the constrained parts. Error propagation analysis shows that this structure gives rise to unstable error propagation in the constrained part. In contrast, the constrained part of the third algorithm preceeds the unconstrained part. It is shown that this algorithm gives an ++exact solution to a linearly constrained least-squares adaptive filtering problem with perturbed constraints and perturbed input data. A minor modification to the constrained part of the linearly constrained QRD-RLS algorithm is proposed to avoid a potential numerical difficulty due to the Gaussian elimination operation employed in the algorithm.
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Callender, Christopher Peter. "Numerically robust implementations of fast recursive least squares adaptive filters using interval arithmetic." Thesis, University of Edinburgh, 1991. http://hdl.handle.net/1842/10853.
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Algorithms have been developed which perform least squares adaptive filtering with great computational efficiency. Unfortunately, the fast recursive least squares (RLS) algorithms all exhibit numerical instability due to finite precision computational errors, resulting in their failure to produce a useful solution after a short number of iterations. In this thesis, a new solution to this instability problem is considered, making use of interval arithmetic. By modifying the algorithm so that upper and lower bounds are placed on all quantities calculated, it is possible to obtain a measure of confidence in the solution calculated by a fast RLS algorithm and if it is subject to a high degree of inaccuracy due to finite precision computational errors, then the algorithm may be rescued, using a reinitialisation procedure. Simulation results show that the stabilised algorithms offer an accuracy of solution comparable with the standard recursive least squares algorithm. Both floating and fixed point implementations of the interval arithmetic method are simulated and long-term stability is demonstrated in both cases. A hardware verification of the simulation results is also performed, using a digital signal processor(DSP). The results from this indicate that the stabilised fast RLS algorithms are suitable for a number of applications requiring high speed, real time adaptive filtering. A design study for a very large scale integration (VLSI) technology coprocessor, which provides hardware support for interval multiplication, is also considered. This device would enable the hardware realisation of a fast RLS algorithm to operate at far greater speed than that obtained by performing interval multiplication using a DSP. Finally, the results presented in this thesis are summarised and the achievements and limitations of the work are identified. Areas for further research are suggested.
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Wood, John D. "MIMO recursive least squares control algorithm for the AN/FPN-44A Loran-C transmitter." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA274820.
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Daniel, Timothy Seth. "The effects of precision on the fast, recursive least-squares transversal filters for adaptive filtering." Thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-03242009-040454/.
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Wang, Dongmei. "Least mean square algorithm implementation using the texas instrument digital signal processing board." Ohio University / OhioLINK, 1999. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1175279376.
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Wang, Jingming. "A recursive least-squares ASIC for broadband 8 x 8 multiple-input multiple-output wireless communications." Diss., Restricted to subscribing institutions, 2005. http://uclibs.org/PID/11984.
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Peacock, Matthew James McKenzie. "Random Matrix Theory Analysis of Fixed and Adaptive Linear Receivers." University of Sydney, 2006. http://hdl.handle.net/2123/985.
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Doctor of Philosophy (PhD)This thesis considers transmission techniques for current and future wireless and mobile communications systems. Many of the results are quite general, however there is a particular focus on code-division multiple-access (CDMA) and multi-input multi-output (MIMO) systems. The thesis provides analytical techniques and results for finding key performance metrics such as signal-to-interference and noise power ratios (SINR) and capacity. This thesis considers a large-system analysis of a general linear matrix-vector communications channel, in order to determine the asymptotic performance of linear fixed and adaptive receivers. Unlike many previous large-system analyses, these results cannot be derived directly from results in the literature. This thesis considers a first-principles analytical approach. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random i.i.d. and random orthogonal precoding. The approach is also used to derive the distribution of sums and products of free random matrices. Expressions for the asymptotic SINR of the MMSE receiver are derived, along with the transient and steady-state SINR of the ALS receiver, trained using either i.i.d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i.d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission.
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Peacock, Matthew James McKenzie. "Random Matrix Theory Analysis of Fixed and Adaptive Linear Receivers." Thesis, The University of Sydney, 2005. http://hdl.handle.net/2123/985.
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This thesis considers transmission techniques for current and future wireless and mobile communications systems. Many of the results are quite general, however there is a particular focus on code-division multiple-access (CDMA) and multi-input multi-output (MIMO) systems. The thesis provides analytical techniques and results for finding key performance metrics such as signal-to-interference and noise power ratios (SINR) and capacity. This thesis considers a large-system analysis of a general linear matrix-vector communications channel, in order to determine the asymptotic performance of linear fixed and adaptive receivers. Unlike many previous large-system analyses, these results cannot be derived directly from results in the literature. This thesis considers a first-principles analytical approach. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random i.i.d. and random orthogonal precoding. The approach is also used to derive the distribution of sums and products of free random matrices. Expressions for the asymptotic SINR of the MMSE receiver are derived, along with the transient and steady-state SINR of the ALS receiver, trained using either i.i.d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i.d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission.
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Felixson, Henrik. "Vehicle Ahead Property Estimation in Heavy Duty Vehicles." Thesis, Linköpings universitet, Reglerteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-108341.
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Zhang, Qi. "Magnetic Rendering: Magnetic Field Control for Haptic Interaction." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32613.
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As a solution to mid-air haptic actuation with strong and continuous tactile force, Magnetic Rendering is presented as an intuitive haptic display method applying an electromagnet array to produce a magnetic field in mid-air where the force field can be felt as magnetic repulsive force exerted on the hand through the attached magnet discs. The magnetic field is generated by a specifically designed electromagnet array driven by direct current. By attaching small magnet discs on the hand, the tactile sensation can be perceived by the user. This method can provide a strong tactile force on multiple points covering user’s hand and avoid cumbersome attachments with wires, thus it is suitable for a co-located visual and haptic display. In my work, the detailed design of the electromagnet array for haptic rendering purposes is introduced, which is modelled and tested using Finite Element Method simulations. The model is characterized mathematically, and three methods for controlling the magnetic field are applied accordingly: direct control, system identification and adaptive control. The performance of the simulated model is evaluated in terms of magnetic field distribution, force strength, operation distance and force stiffness. The control algorithms are implemented and tested on a 3-by-3 and a 15-by-15 model, respectively. Simulations are performed on a 15-by-15 model to generate a haptic human face, which results in a smooth force field and accurate force exertion on the control points.
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Berner, Marcus. "Automatic tuning of Electro-Optical Director." Thesis, KTH, Reglerteknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-105715.
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Directors designed for observation and fire control in naval environments consist of a mechanical pedestal moved by two electrical motors. To meet the high demands on director precision, a servo solution based on feedback control is used. The digital servo controller has to be tuned to meet demands on performance and stability. This report presents methods for automatic tuning, intended to replace today’s manual tuning procedures. System identification based on relay feedback and recursive least-squares approximations are combined with the Ziegler-Nichols and AMIGO tuning procedures for PI controllers are evaluated. Evaluations are performed in simulations, for which a SIMULINK model is constructed. Results indicate that the automatic tuning may perform well compared to the manual tuning used today, and that it could bring considerable reduction in the time required for tuning.
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Madkour, A. A. M., M. Alamgir Hossain, Keshav P. Dahal, and H. Yu. "Real-time system identification using intelligent algorithms." IEEE, 2004. http://hdl.handle.net/10454/2471.
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This research presents an investigation into
the development of real time system identification using
intelligent algorithms. A simulation platform of a flexible
beam vibration using finite difference (FD) method is
used to demonstrate the real time capabilities of the
identification algorithms. A number of approaches and
algorithms for on line system identifications are explored
and evaluated to demonstrate the merits of the algorithms
for real time implementation. These approaches include
identification using (a) traditional recursive least square
(RLS) filter, (b) Genetic Algorithms (GAs) and (c)
adaptive Neuro_Fuzzy (ANFIS) model. The above
algorithms are used to estimate a linear discrete second
order model for the flexible beam vibration. The model is
implemented, tested and validated to evaluate and
demonstrate the merits of the algorithms for real time
system identification. Finally, a comparative performance
of error convergence and real time computational
complexity of the algorithms is presented and discussed
through a set of experiments.
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Lee, Teahyung. "Algorithm-Based Efficient Approaches for Motion Estimation Systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19783.
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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008.Committee Chair: Anderson, David; Committee Member: Gray, Alexander; Committee Member: Ma, Xiaoli; Committee Member: Mersereau , Russell; Committee Member: Wills, Donald.
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Moreira, Giuliana Chaves. "Previsão de níveis fluviais em tempo atual com modelo de regressão adaptativo: aplicação na bacia do rio Uruguai." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/147081.
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Este trabalho avaliou o potencial da aplicação da técnica recursiva dos mínimos quadrados (MQR) para o ajuste em tempo atual dos parâmetros de modelos autorregressivos com variáveis exógenas (ARX), as quais são constituídas pelos níveis de montante para melhorar o desempenho das previsões de níveis fluviais em tempo atual. Três aspectos foram estudados em conjunto: variação do alcance escolhido para a previsão, variação da proporção da área controlada em bacias a montante e variação da área da bacia da seção de previsão. A pesquisa foi realizada em três dimensões principais: a) metodológica (sem recursividade; com recursividade; com recursividade e fator de esquecimento); b) temporal (6 alcances diferentes: 10, 24, 34, 48, 58 e 72 horas); e c) espacial (variação da área controlada da bacia e da área da bacia definida pela seção de previsão). A área de estudo escolhida para essa pesquisa foi a bacia do rio Uruguai com exutório no posto fluviométrico de Uruguaiana (190.000 km²) e as suas sub-bacias embutidas de Itaqui (131.000 km²), Passo São Borja (125.000km²), Garruchos (116.000 km²), Porto Lucena (95.200 km²), Alto Uruguai (82.300 km²) e Iraí (61.900 km²). Os dados de níveis fluviométricos, com leituras diárias às 07:00 e às 17:00 horas, foram fornecidos pela Companhia de Pesquisa de Recursos Minerais (CPRM), sendo utilizados os dados de 1/1/1991 a 30/6/2015. Para a análise de desempenho dos modelos, foi aplicado como estatística de qualidade o coeficiente de Nash-Sutcliffe (NS) e o quantil 0,95 dos erros absolutos (EA(0,95): erro que não foi ultrapassado com a frequência de 0,95). Observou-se que os erros EA(0,95) dos melhores modelos obtidos para cada bacia sempre aumentam com a redução da área controlada, ou seja, a qualidade das previsões diminui com o deslocamento da seção de controle de jusante para montante. O ganho na qualidade das previsões com a utilização dos recursos adaptativos torna-se mais evidente, especialmente quando observam-se os valores de EA(0,95), pois esta estatística é mais sensível, com diferenças maiores em relação ao coeficiente NS. Além disso, este é mais representativo para os erros maiores, que ocorrem justamente durante os eventos de inundações. De modo geral, foi observado que, à medida que diminui a área da bacia, é possível obter previsões com alcances cada vez menores. Porém a influência do tamanho da área controlada de bacias a montante melhora o desempenho de bacias menores quando se observam principalmente os erros EA(0,95). Por outro lado, se a proporção da bacia controlada de montante já é bastante grande, como é o caso das alternativas 1 e 2 utilizadas para previsão em Itaqui (entre 88,5% e 95,4 %, respectivamente), os recursos adaptativos não fazem muita diferença na obtenção de melhores resultados. Todavia, quando se observam bacias com menores áreas de montante controladas, como é o caso de Porto Lucena para a alternativa 2 (65% de área controlada), o ganho no desempenho dos modelos com a utilização dos recursos adaptativos completos (MQR+f.e: mínimos quadrados recursivos com fator de esquecimento) torna-se relevante.This study evaluated the potential of the application of the recursive least squares technique (RLS) to adjust in real time the model parameters of the autoregressive models with exogenous variables (ARX), which consists of the upstream levels, to improve the performance of the forecasts of river levels in real time. Three aspects were studied jointly: the variation of the lead time chosen for the forecast, the variation in the proportion of controlled area in upstream basins and variation in the area of forecasting section of the basin. The research was conducted in three main dimensions: a) methodological (without recursion; with recursion; with recursion and forgetting factor); b) temporal (6 different lead times: 10, 24, 34, 48, 58 and 72 hours); and c) spatial (variation in the controlled area of the basin and the area of the basin defined by the forecast section). The study area chosen for this research was the Uruguay River basin with its outflow at the river gage station of Uruguaiana (190,000 km²) and its entrenched sub-basins in Itaqui (131,000 km²), Passo São Borja (125,000 km²), Garruchos (116,000 km²), Porto Lucena (95,200 km²), Alto Uruguai (82,300 km²), and Iraí (61,900 km²). The river levels data, with daily readings at 7am and 5pm, were provided by the Company of Mineral Resources Research (CPRM), with the data used from January 1, 1991 to June 30, 2015. We applied the Nash-Sutcliffe coefficient (NS) and the quantile 0.95 of absolute errors (EA(0,95): error has not been exceeded at the rate of 0.95) for the analysis of models performances. We observed that the errors EA(0.95) of the best models obtained for each basin always increase with the reduction of the controlled area then the quality of the forecasts decreases with displacement of the downstream control section upstream. The gain in quality of the forecasts with the use of adaptive resources becomes more evident especially when the observed values of EA(0.95) as this statistic is more sensitive with greater differences in relation to the Nash-Sutcliffe Coefficient (NS). Moreover, this is most representative for larger errors which occur precisely during flooding events. In general, we observed that, as much as the area of the basin decreases, it is possible to obtain forecasts with smaller lead times, but the influence of the size of the area controlled upstream basins improves the performance of smaller basins when observing, especially the errors EA (0.95). However, if the proportion of the upstream of controlled basin is already quite large - as in the case of the alternatives 1 and 2 used for forecast in Itaqui (between 88.5% and 95.4%, respectively) - the adaptive resources do not differ too much in getting better results. However, when observing basins with smaller areas controlled upstream - as is the case of Porto Lucena to alternative 2 (65% controlled area) - the performance gain of the models with the use of the complete adaptive resources (MQR+f.e.) becomes relevant.
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Vaňková, Tereza. "Adaptivní regulátory s principy umělé inteligence a jejich porovnání s klasickými metodami identifikace." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-218930.
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Master’s thesis is focused on the adaptive controllers. The first theoretic part mainly describes the parametric identification, which belongs to the most important part of the adaptive controller’s structure. Classical identification methods (the recursive least squares methods) are firstly mentioned and afterwards the identification methods based on the neural network (the Marquardt-Levenberg algorithm and the new identification algorithm NIA inspired by the neural networks) are described. At the conclusion of the theoretic part there are mentioned the algorithm of the adaptive controller’s tuning which uses the identification parameters (the modified Z-N method) and the tested types of adaptive controllers. Particular results, which were found out by verifying of the adaptive controllers on the simulation and real models, are contained in second, the practical, part of the thesis. Finally, achieved results are compared with the classical discrete PID controller and with the adaptive controller of the B&R company.
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Silva, Aurea Aparecida da. "Determinação de órbitas com o GPS através de mínimos quadrados recursivo com rotações de Givens /." Guaratinguetá : [s.n.], 2001. http://hdl.handle.net/11449/91832.
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Resumo: O Sistema de Posicionamento Global oferece um poderoso e relativamente barato processo para se determinar órbitas de satélites artificiais da Terra. Este trabalho apresenta um método de determinação de órbita para satélites com um receptor GPS a bordo. Medidas de pseudo-distância são usadas para estimar o vetor de estado. O estimador considerado é o método dos mínimos quadrados recursivo, através de rotações ortogonais de Givens, com a finalidade de evitar problemas numéricos e de inversão de matrizes. É considerado a modelagem das forças devido ao geopotencial de alto grau e ordem. Resultados indicam que a precisão em posição melhor que 10 m foi obtido usando dados reais do satélite Topex (com um mínimo de duas horas de dados - aproximadamente um período orbital). O resíduo de pseudo-distância teve um desvio padrão cerca de 5 m.Abstract: The Global Positioning System is a powerful and low cost process to compute orbits for some artificial Earth satellites. This work presents a method of orbit determination for satellites with an onboard GPS receiver. Pseudo-ranges are used in the measurements equations for the orbit estimator. The estimator considered is the recursive least squares method, numerically improved with orthogonal Givens rotations and thus avoiding problems concerning inversion of matrices. Up to high order geopotential perturbations are taken into account. Results indicate that precision better than 10 m is easily obtained using batches of one orbital period for the TOPEX satellite (two hours of orbital period). Standard deviation of about 5 m resulted for the residuals.
Orientador: Rodolpho Vilhena de Moraes
Coorientador: Hélio Koiti Kuga
Mestre
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Silva, Aurea Aparecida da [UNESP]. "Determinação de órbitas com o GPS através de mínimos quadrados recursivo com rotações de Givens." Universidade Estadual Paulista (UNESP), 2001. http://hdl.handle.net/11449/91832.
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O Sistema de Posicionamento Global oferece um poderoso e relativamente barato processo para se determinar órbitas de satélites artificiais da Terra. Este trabalho apresenta um método de determinação de órbita para satélites com um receptor GPS a bordo. Medidas de pseudo-distância são usadas para estimar o vetor de estado. O estimador considerado é o método dos mínimos quadrados recursivo, através de rotações ortogonais de Givens, com a finalidade de evitar problemas numéricos e de inversão de matrizes. É considerado a modelagem das forças devido ao geopotencial de alto grau e ordem. Resultados indicam que a precisão em posição melhor que 10 m foi obtido usando dados reais do satélite Topex (com um mínimo de duas horas de dados - aproximadamente um período orbital). O resíduo de pseudo-distância teve um desvio padrão cerca de 5 m.
The Global Positioning System is a powerful and low cost process to compute orbits for some artificial Earth satellites. This work presents a method of orbit determination for satellites with an onboard GPS receiver. Pseudo-ranges are used in the measurements equations for the orbit estimator. The estimator considered is the recursive least squares method, numerically improved with orthogonal Givens rotations and thus avoiding problems concerning inversion of matrices. Up to high order geopotential perturbations are taken into account. Results indicate that precision better than 10 m is easily obtained using batches of one orbital period for the TOPEX satellite (two hours of orbital period). Standard deviation of about 5 m resulted for the residuals.
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Rao, Sughosh J. "Development of a Hardware in the Loop Simulation System for Heavy Truck ESC Evaluation and Trailer Parameter and State Estimation." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1374154113.
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Silva, Paulo César da. "PI-MQR adaptativo aplicado a um motor de indução trifásico utilizando a plataforma DSPACE1103." Universidade do Estado de Santa Catarina, 2015. http://tede.udesc.br/handle/handle/1879.
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Previous issue date: 2015-07-10Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The electrical parameters of three-phase induction motors vary according to their operating point, with the temperature and also with the natural machine degradation. Since the design regulators are typically performed based on linear and simplified equations of the machine, the parametric variation can cause unwanted responses, since the motor behavior is non-linear and time variant. Thus, it is proposed in this work carry the identification of the electrical parameters of the induction motor using the estimator called Least Squares Recursive (RLS). Thus, with the parametric data updated every sampling period can be recalculated in real time the gains of the regulators are designed for controlling the induction machine and make minor mismatches. The experimental results were obtained with the processing performed by dSPACE hardware (DS1103), which has an interface with Matlab/Simulink, facilitating the use by the user and reducing the time taken for testing bench. The results of numerical and practical simulations show a comparison between the mesh proposal, the parametric identification and update of the gains of the controllers (adaptive control) and the mesh with controllers with fixed gains.
Os parâmetros elétricos do motor de indução trifásico variam conforme o seu ponto de operação, com a temperatura e também com a degradação natural da máquina. Visto que o projeto de reguladores são tipicamente realizados com base em equações lineares e simplicadas da máquina, a variação paramétrica pode causar respostas indesejadas, pois o comportamento do motor é não-linear e variante no tempo. Desta forma propõe-se neste trabalho realizar a identificação dos parâmetros elétricos do motor de indução, utilizando o estimador denominado de Mínimos Quadrados Recursivos (MQR). Assim, com os dados paramétricos atualizados a cada período de amostragem, pode-se recalcular em tempo real, os ganhos dos reguladores que são projetados para o controle da máquina de indução e tornar os descasamentos menores. Os resultados experimentais foram obtidos com o processamento realizado pelo hardware dSPACE (DS1103), que possui uma interface com o Matlab/Simulink, facilitando a utilização por parte do usuário e reduzindo o tempo dispendido para os testes em bancada. Os resultados de simulações numéricas e práticos apresentam uma comparação entre a malha proposta, com a identificação paramétrica e atualiza ção dos ganhos dos controladores (controle adaptativo) e a malha com controladores com ganhos fixos.
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Fernandes, Carlos Alexandre Rolim. "EqualizaÃÃo adaptativa e autodidata de canais lineares e nÃo-lineares utilizando o algoritmo do mÃdulo constante." Universidade Federal do CearÃ, 2005. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=2041.
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Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgicoEste trabalho trata da proposiÃÃo de algoritmos para equalizaÃÃo cega de canais lineares e nÃao-lineares inspirados no Algoritmo do MÃdulo Constante (CMA). O CMA funciona de maneira bastante eficiente com constelaÃÃes nas quais todos os pontos possuem a mesma amplitude, como em modulaÃÃes do tipo Phase Shift Keying (PSK). Entretanto, quando os pontos da constelaÃÃo podem assumir diferentes valores de amplitudes, como em modulaÃÃes do tipo Quadrature Amplitude Modulation (QAM), o CMA e seus derivados muitas vezes nÃo funcionam de forma satisfatÃria. Desta forma, as tÃcnicas aqui propostas sÃo projetadas para melhorar a performance do CMA em termos de velocidade de convergÃncia e precisÃo, quando operando em sinais transmitidos com diversos mÃdulos, em particular para a modulaÃÃo QAM. Assim como o CMA, para possuir um bom apelo prÃtico, essas tÃcnicas devem apresentar bom compromisso entre complexidade, robustez e desempenho. Para tanto, as tÃcnicas propostas utilizam o Ãltimo sÃmbolo decidido para definir uma estimaÃÃo de raio de referÃncia para a saÃda do equalizador. De fato, esses algoritmos podem ser vistos como generalizaÃÃes do CMA e de alguns derivados do CMA para constelaÃÃes com mÃltiplos raios. A proposiÃÃo de algoritmos do tipo gradiente estocÃstico à concluÃda com o desenvolvimento de tÃcnicas originais, baseadas no CMA, para equalizaÃÃo de canais do tipo Wiener, que consiste em um filtro linear com memÃria, seguido por um filtro nÃo-linear sem memÃria. As expressÃes para a adaptaÃÃo do equalizador sÃo encontradas com o auxÃlio de uma notaÃÃo unificada para trÃs diferentes estruturas: i) um filtro de Hammerstein; ii) um filtro de Volterra diagonal; e iii) um filtro de Volterra completo. Um estudo teÃrico acerca do comportamento do principal algoritmo proposto, o Decision Directed Modulus Algorithm (DDMA) à realizado. SÃo analisadas a convergÃncia e a estabilidade do algoritmo atravÃs de uma anÃlise dos pontos de mÃnimo de sua funÃÃo custo. Outro objetivo à encontrar o valor teÃrico do Erro MÃdio QuadrÃtico MÃdio em Excesso - Excess Mean Square Error (EMSE) fornecido pelo DDMA considerando-se o caso sem ruÃdo. Ao final, à feito um estudo em que se constata que o algoritmo DDMA possui fortes ligaÃÃes com a soluÃÃo de Wiener e com o CMA. VersÃes normalizadas, bem como versÃes do tipo Recursive Least Squares (RLS), dos algoritmos do tipo gradiente estocÃstico estudados sÃo tambÃm desenvolvidas. Cada famÃlia de algoritmos estudada fie composta por quatro algoritmos com algumas propriedades interessantes e vantagens sobre as tÃcnicas clÃssicas, especialmente quando operando em sinais QAM de ordem elevada. TambÃm sÃo desenvolvidas versÃes normalizadas e do tipo RLS dos algoritmos do tipo CMA estudados para equalizaÃÃo de canais nÃo-lineares. O comportamento de todas as famÃlias de algoritmos desenvolvidos à testado atravÃs de simulaÃÃes computacionais, em que à verificado que as tÃcnicas propostas fornecem ganhos significativos em desempenho, em termos de velocidade de convergÃncia e erro residual, em relaÃÃo Ãs tÃcnicas clÃssicas.
This work studies and proposes algorithms to perform blind equalization of linear and nonlinear channels inspired on the Constant Modulus Algorithm (CMA). The CMA works very well for modulations in which all points of the signal constellation have the same radius, like in Phase Shift Keying (PSK) modulations. However, when the constellation points are characterized by multiple radii, like in Quadrature Amplitude Modulation (QAM) signals, the CMA does not work properly in many situations. Thus, the techniques proposed here are designed to improve the performance of the CMA, in terms of speed of convergence and residual error, when working with signals transmitted with multiple magnitude, in particular with QAM signals. As well as for the CMA, these techniques should have a good compromise among performance, complexity and robustness. To do so, the techniques use the last decided symbol to estimate reference radius to the output of the equalizer. In fact, they can be seen as modifications of the CMA and of some of its derivatives for constellations with multiple radii. The proposition of stochastic gradient algorithms is concluded with the development of new adaptive blind techniques to equalize channels with a Wiener structure. A Wiener filter consists of a linear block with memory followed by a memoryless nonlinearity, by using the CMA. We develop expressions for the adaptation of the equalizer using a unified notation for three different equalizer filter structures: i) a Hammerstein filter, ii) a diagonal Volterra filter and iii) a Volterra filter. A theoretical analysis of the main proposed technique, the Decision Directed Modulus Algorithm (DDMA), is also done. We study the convergence and the stability of the DDMA by means of an analysis of the minima of the DDM cost function. We also develop an analytic expression for the Excess Mean Square Error (EMSE) provided by the DDMA in the noiseless case. Then, we nd some interesting relationships among the DDM, the CM and the Wiener cost functions. We also develop a class of normalized algorithms and a class of Recursive Least Squares (RLS)-type algorithms for blind equalization inspired on the CMA-based techniques studied. Each family is composed of four algorithms with desirable properties and advantages over the original CM algorithms, specially when working with high-level QAM signals. Normalized and RLS techniques for equalization of Wiener channels are also developed. The behavior of the proposed classes of algorithms discussed is tested by computational simulations. We verify that the proposed techniques provide significative gains in performance, in terms of speed of convergence and residual error, when compared to the classical algorithms.
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Srar, Jalal Abdulsayed. "Adaptive antenna array beamforming using a concatenation of recursive least square and least mean square algorithms." Thesis, Curtin University, 2011. http://hdl.handle.net/20.500.11937/618.
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In recent years, adaptive or smart antennas have become a key component for various wireless applications, such as radar, sonar and cellular mobile communications including worldwide interoperability for microwave access (WiMAX). They lead to an increase in the detection range of radar and sonar systems, and the capacity of mobile radio communication systems. These antennas are used as spatial filters for receiving the desired signals coming from a specific direction or directions, while minimizing the reception of unwanted signals emanating from other directions.Because of its simplicity and robustness, the LMS algorithm has become one of the most popular adaptive signal processing techniques adopted in many applications, including antenna array beamforming. Over the last three decades, several improvements have been proposed to speed up the convergence of the LMS algorithm. These include the normalized-LMS (NLMS), variable-length LMS algorithm, transform domain algorithms, and more recently the constrained-stability LMS (CSLMS) algorithm and modified robust variable step size LMS (MRVSS) algorithm. Yet another approach for attempting to speed up the convergence of the LMS algorithm without having to sacrifice too much of its error floor performance, is through the use of a variable step size LMS (VSSLMS) algorithm. All the published VSSLMS algorithms make use of an initial large adaptation step size to speed up the convergence. Upon approaching the steady state, smaller step sizes are then introduced to decrease the level of adjustment, hence maintaining a lower error floor. This convergence improvement of the LMS algorithm increases its complexity from 2N in the case of LMS algorithm to 9N in the case of the MRVSS algorithm, where N is the number of array elements.An alternative to the LMS algorithm is the RLS algorithm. Although higher complexity is required for the RLS algorithm compared to the LMS algorithm, it can achieve faster convergence, thus, better performance compared to the LMS algorithm. There are also improvements that have been made to the RLS algorithm families to enhance tracking ability as well as stability. Examples are, the adaptive forgetting factor RLS algorithm (AFF-RLS), variable forgetting factor RLS (VFFRLS) and the extended recursive least squares (EX-KRLS) algorithm. The multiplication complexity of VFFRLS, AFF-RLS and EX-KRLS algorithms are 2.5N2 + 3N + 20 , 9N2 + 7N , and 15N3 + 7N2 + 2N + 4 respectively, while the RLS algorithm requires 2.5N2 + 3N .All the above well known algorithms require an accurate reference signal for their proper operation. In some cases, several additional operating parameters should be specified. For example, MRVSS needs twelve predefined parameters. As a result, its performance highly depends on the input signal.In this study, two adaptive beamforming algorithms have been proposed. They are called recursive least square - least mean square (RLMS) algorithm, and least mean square - least mean square (LLMS) algorithm. These algorithms have been proposed for meeting future beamforming requirements, such as very high convergence rate, robust to noise and flexible modes of operation. The RLMS algorithm makes use of two individual algorithm stages, based on the RLS and LMS algorithms, connected in tandem via an array image vector. On the other hand, the LLMS algorithm is a simpler version of the RLMS algorithm. It makes use of two LMS algorithm stages instead of the RLS – LMS combination as used in the RLMS algorithm.Unlike other adaptive beamforming algorithms, for both of these algorithms, the error signal of the second algorithm stage is fed back and combined with the error signal of the first algorithm stage to form an overall error signal for use update the tap weights of the first algorithm stage.Upon convergence, usually after few iterations, the proposed algorithms can be switched to the self-referencing mode. In this mode, the entire algorithm outputs are swapped, replacing their reference signals. In moving target applications, the array image vector, F, should also be updated to the new position. This scenario is also studied for both proposed algorithms. A simple and effective method for calculate the required array image vector is also proposed. Moreover, since the RLMS and the LLMS algorithms employ the array image vector in their operation, they can be used to generate fixed beams by pre-setting the values of the array image vector to the specified direction.The convergence of RLMS and LLMS algorithms is analyzed for two different operation modes; namely with external reference or self-referencing. Array image vector calculations, ranges of step sizes values for stable operation, fixed beam generation, and fixed-point arithmetic have also been studied in this thesis. All of these analyses have been confirmed by computer simulations for different signal conditions. Computer simulation results show that both proposed algorithms are superior in convergence performances to the algorithms, such as the CSLMS, MRVSS, LMS, VFFRLS and RLS algorithms, and are quite insensitive to variations in input SNR and the actual step size values used. Furthermore, RLMS and LLMS algorithms remain stable even when their reference signals are corrupted by additive white Gaussian noise (AWGN). In addition, they are robust when operating in the presence of Rayleigh fading. Finally, the fidelity of the signal at the output of the proposed algorithms beamformers is demonstrated by means of the resultant values of error vector magnitude (EVM), and scatter plots. It is also shown that, the implementation of an eight element uniform linear array using the proposed algorithms with a wordlength of nine bits is sufficient to achieve performance close to that provided by full precision.
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Faltus, Ivo. "Adaptivní regulátory pro systémy s dopravním zpožděním a jejich porovnání s klasickými pevně nastavenými regulátory." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-219933.
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Master thesis is focused on the philosophy of design adaptive controller. In the theoretic part are described parts of the adaptive controller, which belongs parts as online identification by recursive least-squares method and PSD controller, which can set its parameters according to identified system (use Z-N method). The part of control system with transport delay is situated at the conclusion of the theoretic part, there are focused on Smith predictor. Practical part is focused on verification of all algorithms, which was performed on models and real systems.
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Krykorka, Daniel. "Adaptivní regulátory pro systémy s dopravním zpožděním a jejich porovnání s klasickými pevně nastavenými parametry regulátorů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-221004.
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Master thesis is focused on the philosophy of design adaptive controller. In the theoretic part are described parts of the adaptive controller, which belongs parts as online identification by recursive least-squares method and PSD controller, which can set its parameters according to identified system (use Z-N method). The part of control system with transport delay is situated at the conclusion of the theoretic part, there are focused on Smith predictor. Practical part is focused on verification of all algorithms, which was performed on models and real systems.
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Nyberg, Tobias. "Torque-Based Load Estimation for Passenger Vehicles." Thesis, Linköpings universitet, Reglerteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-179208.
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An accurate estimate of the mass of a passenger vehicle is important for several safety systems and environmental aspects. In this thesis, an algorithm for estimating the mass of a passenger vehicle using the recursive least squares methodis presented. The algorithm is based on a physical model of the vehicle and is designed to be able to run in real-time onboard a vehicle and uses the wheel torque signal calculated in the electrical control unit in the engine. Therefore no estimation of the powertrain is needed. This is one contribution that distinguishes this thesis from previous work on the same topic, which has used the engine torque. The benefit of this is that no estimation of the dynamics in the powertrain is needed. The drawback of using this method is that the algorithm is dependenton the accuracy of the estimation done in the engine electrical control unit. Two different versions of the recursive least squares method (RLS) have been developed - one with a single forgetting factor and one with two forgetting factors. The estimation performance of the two versions are compared on several different real-world driving scenarios, which include driving on country roads, highways, and city roads, and different loads in the vehicle. The algorithm with a single forgetting factor estimates the mass with an average error for all tests of 4.42% and the algorithm with multiple forgetting factors estimates the mass with an average error of 4.15 %, which is in line with state-of-the-art algorithms that are presented in other studies. In a sensitivity analysis, it is shown that the algorithms are robust to changes in the drag coefficient. The single forgetting factor algorithm is robust to changes in the rolling resistance coefficient whereas the multiple forgetting factor algorithm needs the rolling resistance coefficient to be estimated with fairly good accuracy. Both versions of the algorithm need to know the wheel radius with an accuracy of 90 %. The results show that the algorithms estimate the mass accurately for all three different driving scenarios and estimate highway roads best with an average error of 2.83 % and 2.69 % for the single forgetting factor algorithm and the multiple forgetting factor algorithm, respectively. The results indicate it is possible to use either algorithm in a real-world scenario, where the choice of which algorithm depends on sought-after robustness.
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Staub, Ruben. "Développement d'outils de modélisation des surfaces d'alliages et leur application à la cinétique en catalyse hétérogène." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN059.
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Cette thèse se focalise sur le développement d’outils pour l’étude fondamentale des interactions latérales au travers de multiples projets : D’un point de vue quantique, les effets énergétiques des interactions chimiques sont décomposables rigoureusement en utilisant des orbitales moléculaires absolument localisées (ALMO). Au cours de cette thèse, une approximation de champ moyen a été développée et implémentée dans CP2K afin d’unifier le formalisme ALMO avec la théorie des états mixtes dans une description DFT, permettant d’étendre l’analyse en composantes énergétiques aux systèmes métalliques.D’un point de vue purement topologique, un nouvel algorithme de détermination de liaisons chimiques (ASANN) a été développé durant cette thèse. Au travers d’un simple terme correctif, ASANN étend l’algorithme de référence SANN aux systèmes présentant une anisotropie locale, sans introduire aucun paramètre. Les nombres de coordination ainsi produits sont particulièrement adaptés pour la descriptions d’interfaces. Ces points de vue complémentaires se combinent sous la forme d’un Hamiltonien effectif basé sur les interactions latérales. Un nouvel outil non-stochastique a été développé et implémenté durant cette thèse, utilisant des algorithmes d’apprentissage par renforcement pour l’entraînement automatique de tels modèles destinés à simuler un système à N corps sur surface réactive. Cet outil repose sur l’adaptation d’un UCT avec une pré-exploration guidée par le modèle en cours d’apprentissage. La mise à jour d’un tel modèle linéaire a été optimisée par la formulation d’un nouvel algorithme de résolution des moindres carrés récursifs exploitant les déficiences de rangChemical bonding can be described using the density functional theory (DFT) framework as electronic density reorganisation between chemical entities. Relying on Absolutely Localized Molecular Orbitals (ALMO), the density reorganization can be separated into polarization and charge transfer. However, the ALMO formalism is intractable when combined with mixed-states theory, which is required for describing metals. As shown herein, these two theories can be unified into a mean-field approximation called S-ALMO, allowing for a fundamental density-based description of most chemical bonds. In practice, bonds are most often defined by geometrical considerations. Based on an intuitive and powerful idea (an atom’s nearest neighbours must cover its field of view), SANN (Solid Angle based Nearest Neighbours) provides with locally adaptive parameter-free coordination numbers. A natural extension of this algorithm, called ASANN, is developed to tackle local anisotropy while remaining parameter-free. We demonstrate that this method effectively provides with a fundamental topology-based definition of coordination numbers applicable to close packed bulks, liquids and interfaces. Even though bonds are topologically defined, they contain chemically relevant information, providing descriptors for describing the associated energy. Lattice-based cluster expansion model Hamiltonians are particularly popular for determining the adsorption energy in heterogeneous catalysis. Fitting the corresponding model Hamiltonian is usually performed on a training set composed of hundreds of structures hand-picked by a chemist. For the model Hamiltonian to be relevant for describing a given reaction, the chemist uses his own expertise and chemical intuition to select a diverse set of chemically relevant structures. Treating the generation of a relevant input as a strategy-based game, a novel active learning scheme for model Hamiltonians is designed based on a UCT (Upper Confidence Tree). Updating the model Hamiltonian on-the-fly is achieved by a novel recursive least-squares algorithm, called rank-Greville, exploiting the rank deficiencies of the occurrence matrix to reduce the scaling of the update. Furthermore, a domain knowledge extension on top of the UCT framework allows to optimize the training set construction, leading to the Reinforcement Sampling scheme. This approach effectively replaces chemical intuition with reproducible reinforcement learning techniques
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Campos, José Carlos Teles. "Filtragem robusta para sistemas singulares discretos no tempo." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-07102015-150651/.
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Esta tese apresenta novos algoritmos que resolvem problemas de estimativas filtrada, suavizadora e preditora para sistemas singulares no tempo discreto usando apenas argumentos determinísticos. Cada capítulo aborda inicialmente as estimativas para o sistema nominal e em seguida, as versões robustas para o sistema com incertezas limitadas. Os resultados encontrados podem ser aplicados tanto em sistemas invariantes como variantes no tempo discreto, utilizando a mesma estrutura do filtro de Kalman. Nos últimos anos, uma quantidade significativa de trabalhos envolvendo estimativas singulares foi publicada enfocando apenas a estimativa filtrada sob a justificativa de que a estimativa preditora era de significativa complexidade quando modelada pelo método dos mínimos quadrados. Por este motivo, poucos trabalhos, como NIKOUKHAH et al. (1992) e ZHANG et al. (1998), deduziram a estimativa preditora. Este último artigo apresentou também um algoritmo para a estimativa suavizadora, mas usando o modelo de inovação ARMA. No entanto, até onde foi possível identificar, nenhum trabalho até agora resolveu o problema de estimativa robusta, considerando incertezas nos parâmetros, para sistemas singulares. Para a dedução das estimativas singulares robustas, esta tese tomou como base SAYED (2001), que deduz o filtro de Kalman robusto com incertezas limitadas utilizando uma abordagem determinística, o chamado filtro BDU. Os filtros robustos para sistemas singulares apresentados nesta tese, são mais abrangentes que os apresentados em SAYED (2001). Quando particularizados para o espaço de estados sem incertezas, todos os filtros se assemelham ao filtro de Kalman.New algorithms to optimal recursive filtering, smoothed and prediction for general time-invariant or time-variant descriptor systems are proposed in this thesis. The estimation problem is addressed as an optimal deterministic trajectory fitting. This problem is solved using exclusively deterministic arguments for systems with or without uncertainties. Kalman type recursive algorithms for robust filtered, predicted and smoothed estimations are derived. In the last years, many papers have paid attention to the estimation problems of linear singular systems. Unfortunately, all those works were concentrated only on the study of filtering problems, for nominal systems. The predicted and smoothed filters are more involved and were considered only by few works : NIKOUKHAH et al. (1992) and ZHANG et al. (1998) had proposed a unified approach for filtering, prediction and smoothing problems which were derived by using the projection formula and were calculated based on the ARMA innovation model, but they had not considered the uncertainties. In this thesis its applied for descriptor systems a robust procedure for usual state space systems developed by SAYED (2001), called BDU filter. It is obtained a robust descriptor Kalman type recursions for filtered, predicted and smoothed estimates. Considering the nominal state space, all descriptor filters developed in this work collapse to the Kalman filter.
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Sladká, Pavla. "Využití rekurzivní metody nejmenších čtverců pro analýzu dynamiky vozidel." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2010. http://www.nusl.cz/ntk/nusl-229022.
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Tato diplomová práce nastiňuje teoretické základy potřebné pro návrh algoritmu rekurzivní metody nejmenších čtverců a následně jeho aplikaci na experimentální data naměřená při testovacím manévru uskutečněném v roce 2001. Analyzována byla příčná dynamika jednostopého rovinného modelu vozidla. Práce také obsahuje srovnání výsledků získaných jednak rekurzivním algoritmem a dále i algoritmem Kalmanova filtru.
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Mendes, Ellon Paiva. "Identifica??o em tempo real de modelo din?mico de rob? m?vel com acionamento diferencial e zona morta." Universidade Federal do Rio Grande do Norte, 2012. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15387.
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Previous issue date: 2012-01-27Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico
Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters
V?rios rob?s m?veis apresentam comportamentos n?o-lineares, principalmente ocasionados por fen?menos de atrito entre as partes mec?nicas do rob? ou entre o rob? e o solo. Modelagens puramente lineares apresentam-se eficientes em alguns casos, mas ? preciso levar em considera??o as n?o-linearidades do rob? quando se deseja movimentos ou posicionamentos precisos. Este trabalho prop?e um procedimento de identifica??o param?trica do modelo de um rob? m?vel com acionamento diferencial, no qual s?o consideradas as n?o-linearidades do tipo zona-morta presentes nos atuadores do rob?. A proposta baseia-se no modelo de Hammerstein para dividir o sistema em blocos lineares e n?o-lineares. O princ?pio da separa??o do termo chave ? utilizado para demonstrar a rela??o entre as entradas e sa?das do sistema com os par?metros tanto da parcela linear quanto da n?o-linear. Os par?metros de ambas as parcelas s?o identificados simultaneamente, atrav?s de um algoritmo de m?nimos quadrados recursivo. Os resultados mostram que ? poss?vel identificar o valor os limites da zona-morta assim como os par?metros da parcela linear do modelo do sistema
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Maciel, Allan James Ferreira. "CONVERGÊNCIA DO ESTIMADOR RLS PARA ALGORITMOS DE PROGRAMAÇÃO DINÂMICA HEURÍSTICA." Universidade Federal do Maranhão, 2012. http://tedebc.ufma.br:8080/jspui/handle/tede/494.
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Previous issue date: 2012-09-28Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The union of methodologies for optimal control and dynamics programming has stimulated the development of algorithms for realization of discrete control systems of the type linear quadratic regulator (DLQR). The methodology is based on reinforcement learning methods based on temporal differences and approximate dynamic programming. The proposed method combines the approach of the value function by method RLS (recursive least squares) and approximate policy iteration schemes heuristic dynamic programming (HDP). The approach is directed to the assessment of convergence of the solution DLQR and the heuristic weighting matrices and of the utility function associated with DLQR. The investigation of convergence properties related to consistency, persistent excitation and polarization of the RLS estimator is performed. The methodology involved in a project achievements online DLQR controllers and is evaluated in a fourth order multivariable dynamic system.
A união das metodologias de controle ótimo e de programação dinâmica tem impulsionado o desenvolvimento de algoritmos para realizações de sistemas de controle discreto do tipo regulador linear quadrático (DLQR). A metodologia utilizada neste trabalho é fundamentada sobre métodos de aprendizagem por reforço baseados em diferenças temporais e programação dinâmica aproximada. O método proposto combina a aproximação da função valor através do método RLS (mínimos quadrados recursivos) e iteração de política aproximada em esquemas de programação dinâmica heurística (HDP). A abordagem é orientada para a avaliação da convergência da solução DLQR e para a sintonia heurística das matrizes de ponderação e da função de utilidade associada ao DLQR. É realizada a investigação das propriedades de convergência relacionadas à consistência, excitação persistente e polarização do estimador RLS. A metodologia contempla realizações de projetos de forma online de controladores DLQR e é avaliada em um sistema dinâmico multivariável de quarta ordem.
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Djaneye-Boundjou, Ouboti Seydou Eyanaa. "Discrete-time Concurrent Learning for System Identification and Applications: Leveraging Memory Usage for Good Learning." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton151298579862899.
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Burlak, Vladimír. "Adaptivní optimální regulátory s principy umělé inteligence v prostředí MATLAB - B&R." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218358.
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This master's thesis considers adaptive optimal controllers. It shows principles of optimal controllers, recursive identification using least-mean squares method and identification based on neural network.
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Badaoui, Noad. "Dynamique et estimation paramétrique pour les gyroscopes laser à milieu amplificateur gazeux." Thesis, Paris Sciences et Lettres (ComUE), 2016. http://www.theses.fr/2016PSLEM058/document.
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Les gyroscopes laser à gaz constituent une solution technique de haute performances dans les problématiques de navigation inertielle. Néanmoins, pour de très faibles vitesses de rotation, les petites imperfections des miroirs de la cavité optique font que les deux faisceaux contra-propageant sont verrouillés en phase. En conséquence, les mesures en quadrature de leur différence de phase ne permettent plus de remonter directement aux vitesses de rotation à l'intérieur d'une zone autour de zéro, dite zone aveugle statique, ou, si l'on utilise une procédure d'activation mécanique, dite zone aveugle dynamique. Ce travail montre qu'il est néanmoins possible, en utilisant des méthodes issues du filtrage et de l'estimation, de remonter aux vitesses de rotation mêmes si ces dernières sont en zone aveugle. Pour cela, on part d'une modélisation physique de la dynamique que l'on simplifie par des techniques de perturbations singulières pour en déduire une généralisation des équations de Lamb. Il s'agit de quatre équations différentielles non-linéaires qui décrivent la dynamique des intensités et des phases des deux faisceaux contra-propageant. Une étude qualitative par perturbations régulières, stabilité exponentielle des points d'équilibre et applications de Poincaré permet de caractériser les zones aveugles statiques et dynamiques en fonction des imperfections dues aux miroirs. Il est alors possible d'estimer en ligne avec un observateur asymptotique fondé sur les moindre carrés récursifs ces imperfections en rajoutant aux deux mesures en quadrature celles des deux intensités. La connaissance précise de ces imperfections permet alors de les compenser dans la dynamique de la phase relative, et ainsi d'estimer les rotations en zone aveugle. Des simulations numériques détaillées illustrent l'intérêt de ces observateurs pour augmenter la précision des gyroscopes à gazGaz ring laser gyroscopes provide a high performance technical solution for inertial navigation. However, for very low rotational speeds, the mirrors imperfections of the optical cavity induce a locking phenomena between the phases of the two counter-propagating Laser beams. Hence, the measurements of the phase difference can no longer be used when the speed is within an area around zero, called lock-in zone, or,if a procedure of mechanical dithering is implemented, dithering lock-in zone. Nevertheless, this work shows that it is possible using filtering and estimation methods to measure the speed even within the lock-in zones. To achieve this result, we exploit a physical modeling of the dynamics that we simplify, using singular perturbation techniques, to obtain a generalization of Lamb's equations. There are four non-linear differential equations describing the dynamics of the intensities and phases of the two counter-propagating beams. A qualitative study by regular perturbation theory, exponential stability of the equilibrium points and Poincaré maps allows a characterisation of the lock-in zones according to the mirrors imperfections. It is then possible to estimate online, with an asymptotic observer based on recursive least squares, these imperfections by considering the additional measurements of the beam intensities. Accurate knowledge of these imperfections enables us to compensate them in the dynamic of the relative phase, and thus to estimate rotational speeds within the lock-in zones. Detailed numerical simulations illustrate the interest of those observers to increase the accuracy of gas ring laser gyroscopes
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Ferreira, Ernesto Franklin Marçal. "Melhorias de estabilidade numérica e custo computacional de aproximadores de funções valor de estado baseados em estimadores RLS para projeto online de sistemas de controle HDP-DLQR." Universidade Federal do Maranhão, 2016. http://tedebc.ufma.br:8080/jspui/handle/tede/1687.
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The development and the numerical stability analysis of a new adaptive critic algorithm to approximate the state-value function for online discrete linear quadratic regulator (DLQR) optimal control system design based on heuristic dynamic programming (HDP) are presented in this work. The proposed algorithm makes use of unitary transformations and QR decomposition methods to improve the online learning e-ciency in the critic network through the recursive least-squares (RLS) approach. The developed learning strategy provides computational performance improvements in terms of numerical stability and computational cost which aim at making possible the implementations in real time of optimal control design methodology based upon actor-critic reinforcement learning paradigms. The convergence behavior and numerical stability of the proposed online algorithm, called RLSµ-QR-HDP-DLQR, are evaluated by computational simulations in three Multiple-Input and Multiple-Output (MIMO) models, that represent the automatic pilot of an F-16 aircraft of third order, a fourth order RLC circuit with two input voltages and two controllable voltage levels, and a doubly-fed induction generator with six inputs and six outputs for wind energy conversion systems.
Neste trabalho, apresenta-se o desenvolvimento e a análise da estabilidade numérica de um novo algoritmo crítico adaptativo para aproximar a função valor de estado para o projeto do sistema de controle ótimo online, utilizando o regulador linear quadrático discreto (DLQR), com base em programação dinâmica heurística (HDP). O algoritmo proposto faz uso de transformações unitárias e métodos de decomposição QR para melhorar a e-ciência da aprendizagem online na rede crítica por meio da abordagem dos mínimos quadrados recursivos (RLS). A estratégia de aprendizagem desenvolvida fornece melhorias no desempenho computacional em termos de estabilidade numérica e custo computacional, que visam tornar possíveis as implementações em tempo real da metodologia do projeto de controle ótimo com base em paradigmas de aprendizado por reforço ator-crítico. O comportamento de convergência e estabilidade numérica do algoritmo online proposto, denominado RLSµ-QR-HDP-DLQR, são avaliados por meio de simulações computacionais em três modelos Múltiplas-Entradas e Múltiplas-Saídas (MIMO), que representam o piloto automático de uma aeronave F-16 de terceira ordem, um circuito de quarta ordem RLC com duas tensões de entrada e dois níveis de tensão controláveis, e um gerador de indução duplamente alimentados com seis entradas e seis saídas para sistemas de conversão de energia eólica.
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Dokoupil, Jakub. "Rozšířená kvadraticky optimální identifikace a filtrace." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-233562.
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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).
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Vávra, Pavel. "Průmyslový regulátor PID s autotunerem a vizualizací." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218359.
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This thesis deals with implementation of industrial used controlling block into Power Panel equipment of B&R in integrated development environment Automation Studio 3.0.71. It is PID controller with autotuner and visualization, which allowed bumpless transfer among controlling algorithms and manual control. PID and I-PD controllers with filtering of derivative action and dynamic antiwindup were implemented. Parameters of PID controller is possible to tune with the aid of ultimate gain and ultimate period according rules of Ziegler-Nichols. Ultimate parameters of controlled plant is possible to acquire with the aid of two identification methods, recursive least squares method and relay feedback. Recursive least squares method was implemented with directional forgetting. For relay feedback were used two types of relays: ideal and saturation relay for improving accuracy of searched ultimate values. The whole solution is programmed in ANSI C which Automation Studio supports. Created controller is control with the aid of touchscreen which is integrated in Power Panel. Trends of process values are viewed on the screen too. For comparison adaptive controller by B&R was implemented. This contoller is standardly supplied with Automation Studio in LoopConR library. All created algorithms were first validated on mathematical model of plant and then on real model in laboratory. The first part of thesis deals with theoretic analysis of used methods. The practical realization is described in the second part of this diploma thesis.
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RÊGO, Patrícia Helena Moraes. "Aprendizagem por Reforço e Programação Dinâmica Aproximada para Controle Ótimo: Uma Abordagem para o Projeto Online do Regulador Linear Quadrático Discreto com Programação Dinâmica Heurística Dependente de Estado e Ação." Universidade Federal do Maranhão, 2014. http://tedebc.ufma.br:8080/jspui/handle/tede/1879.
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In this thesis a proposal of an uni ed approach of dynamic programming, reinforcement learning and function approximation theories aiming at the development of methods and algorithms for design of optimal control systems is presented. This approach is presented in the approximate dynamic programming context that allows approximating the optimal feedback solution as to reduce the computational complexity associated to the conventional dynamic programming methods for optimal control of multivariable systems. Speci cally, in the state and action dependent heuristic dynamic programming framework, this proposal is oriented for the development of online approximated solutions, numerically stable, of the Riccati-type Hamilton-Jacobi-Bellman equation associated to the discrete linear quadratic regulator problem which is based on a formulation that combines value function estimates by means of a RLS (Recursive Least-Squares) structure, temporal di erences and policy improvements. The development of the proposed methodologies, in this work, is focused mainly on the UDU T factorization that is inserted in this framework to improve the RLS estimation process of optimal decision policies of the discrete linear quadratic regulator, by circumventing convergence and numerical stability problems related to the covariance matrix ill-conditioning of the RLS approach.
Apresenta-se nesta tese uma proposta de uma abordagem uni cada de teorias de programação dinâmica, aprendizagem por reforço e aproximação de função que tem por objetivo o desenvolvimento de métodos e algoritmos para projeto online de sistemas de controle ótimo. Esta abordagem é apresentada no contexto de programação dinâmica aproximada que permite aproximar a solução de realimentação ótima de modo a reduzir a complexidade computacional associada com métodos convencionais de programação dinâmica para controle ótimo de sistemas multivariáveis. Especi camente, no quadro de programação dinâmica heurística e programação dinâmica heurística dependente de ação, esta proposta é orientada para o desenvolvimento de soluções aproximadas online, numericamente estáveis, da equação de Hamilton-Jacobi-Bellman do tipo Riccati associada ao problema do regulador linear quadrático discreto que tem por base uma formulação que combina estimativas da função valor por meio de uma estrutura RLS (do inglês Recursive Least-Squares), diferenças temporais e melhorias de política. O desenvolvimento das metodologias propostas, neste trabalho, tem seu foco principal voltado para a fatoração UDU T que é inserida neste quadro para melhorar o processo de estimação RLS de políticas de decisão ótimas do regulador linear quadrá- tico discreto, contornando-se problemas de convergência e estabilidade numérica relacionados com o mal condicionamento da matriz de covariância da abordagem RLS.
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Kalivoda, Jakub. "Adaptivní řízení varny malého pivovaru." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220959.
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This final thesis deals with adaptive control of small brewery. Contains a short description of brewing technology and adaptive control. Includes design of small brawery and control system based on STM32F407 Cortex-M4 microcontroller. For online identification is used Recursive Least Squares Method. The controller function perform a modified PSD controller with filtered derivative component, reducing the first overshot and dynamic antiwindup. The proposed adaptive controller is implemented into microcontroller. Created device i used for semi-automatic beer production.
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Doheny, David A. "Real Time Digital Signal Processing Adaptive Filters for Correlated Noise Reduction in Ring Laser Gyro Inertial Systems." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000306.
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Trespalacios, Pérez Manuel Guillermo 1983. "Contribuição computacional para o método de mínimos quadrados recursivo e aplicações a múltiplas séries temporais." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259119.
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Orientador: Gilmar BarretoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: Esta tese apresenta uma contribuição computacional para o método de mínimos quadrados recursivo (MQR) e a sua aplicação às múltiplas séries temporais. O objetivo principal é obter estimativas com menor erro médio final, em comparação com as estimativas resultantes da aplicação do método MQR usual. Os resultados das análises foram obtidos aplicando diferentes modificações e ajustes no modelo de dados de entrada e saída. Estes ajustes procuram ter a quantidade suficiente de dados nas séries temporais de entrada que forneçam a melhor relação com a série temporal de saída. O método desenvolvido usa inicialmente, e de forma independente, o método MQR em duas matrizes geradas pelo modelo de dados de entrada e saída, obtendo assim dois estimadores do mesmo modelo; a primeira matriz é composta pela totalidade dos dados do modelo final e a segunda matriz é gerada por um filtro que utiliza a primeira matriz e a nova observação, filtro especificado no presente trabalho. Os dois estimadores calculados para cada nova observação são comparados aplicando-lhes critérios estabelecidos neste trabalho, gerando assim um terceiro estimador que _e o melhor estimador do modelo de dados de entrada e saída. O método proposto é chamado de método de mínimos quadrados recursivo 3 (MQR3). Finalmente o método MQR3 _e testado com um modelamento de dados de múltiplas séries temporais e seus resultados comparados com os resultados do método MQR. As estatísticas encontradas para diferentes dados de validação mostram estimativas com menor erro médio final para o método MQR3
Abstract: This thesis presents a computational contribution to the recursive least squares method (RLS) and the application to multiple time series. The main objective is to obtain estimates with lower mean final error, when compared to the estimates resulting from the application of the normal MQR method. The analysis results were obtained by applying different modifications and adjustments to the input and output data model. These adjustments seek to have a sufficient amount of data in the incoming time series to provide the highest ratio with the output time series. The method initially uses, independently, the RLS method in two arrays generated by the input and output data model, thus obtaining two estimators of the same model, the first matrix is composed of all of the data for the final model and the second matrix is generated by a filter that uses the first array and the new observation, filter specified in the present work. The two estimators calculated for each new observation are compared by applying them with criteria established in this work, thereby generating a third which is the best estimator of the input and output model. The proposed method is called recursive least squares method 3 (MQR3). Finally, the method is tested with a MQR3 multiple time series data modeling and the results compared with the results of the RLS method. The statistics found for deferent validation data show estimates with a lower final average error for the MQR3 method
Mestrado
Automação
Mestre em Engenharia Elétrica
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Samek, Martin. "Adaptivní optimální regulátory s principy umělé inteligence v prostředí MATLAB - B&R." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218211.
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Master’s thesis describes adaptive optimal controller design and it’s settings. Identification with principles of artificial intelligence and recursive least squares identification with exponential and directional forgetting are compared separately and as part of controller. Adaptive optimal controller is tested on physical model and compared with solidly adjusted PSD controller. Possibilities of implementation of adaptive optimal controller into programmable logic controller B&R are show and tested.
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Ferreira, Ronaldo Rocha. "Estimação fasorial utilizando técnica recursiva dos mínimos quadrados." reponame:Repositório Institucional da UFABC, 2014.
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Orientador: Prof. Dr. Fabiano Fragoso CostaDissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2014.
Este trabalho propõe um algoritmo de estimaçãoo fasorial baseado na versão modificada do algoritmo de mínimos quadrados recursivo. Este algoritmo é adequado para proteção de sistemas de potência, uma vez que sua resposta é rapida e robusta 'a presença da componente dc de decaimento exponencial, que é uma interferência comum em condi¸ções de falta atrasando a convergência da estimativa fasorial. Além disso, esta dissertação também investiga o uso do chamado método de Prony, a fim de auxiliar e acelerar a convergência da estimação fasorial do algoritmo dos mínimos quadrados. O método de Prony determina o decaimento exponencial a ser extraído do sinal analisado. As técnicas desenvolvidas nessa disserta¸c¿ao foram comparadas com o tradicional estimador de Fourier de um ciclo atrav'es de simula¸c¿oes realizadas em Matlab e de experimentos realizados com um processador de sinais e um amplificador de sinais. Os resultados mostram melhorias da t'ecnica proposta em comparação ao algoritmo de Fourier e incentivam futuras pesquisas relacionadas a este assunto.
This work proposes a phasor estimation algorithm based on a modified recursive least-squares. This algorithm is suitable for power systems protection once its response quick and robust to the decaying dc component, which is a most usual interference in fault conditions and delays the phasor estimation convergence. Furthermore, this dissertation also investigates the usage of the so-called Prony¿s method in order to aid and to speed up the least-squares phasor estimation convergence. This method determines the exponential decaying to be extracted out of the analyzed signal. The present developed techniques have been compared with the traditional one-cycle Fourier estimation by simulation performed on Matlab and by experiments accomplished with a digital signal processor and a signal amplifier. The results show improvements of the proposed techniques over the Fourier algorithm and encourage further research in this topic.