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Frequency Tracking and Phasor Estimation Using Least Squares and Total Least Squares AlgorithmsGuo, Hengdao 01 January 2014 (has links)
System stability plays an important role in electric power systems. With the development of electric power system, the scale of the electric grid is now becoming larger and larger, and many renewable energy resources are integrated in the grid. However, at the same time, the stability and safety issues of electric power system are becoming more complicated. Frequency and phasors are two critical parameters of the system stability. Obtaining these two parameters have been great challenges for decades. Researchers have provided various kinds of algorithms for frequency tracking and phasor estimation. Among them, Least Squares (LS) algorithm is one of the most commonly used algorithm. This thesis studies the LS algorithm and the Total Least Squares (TLS) algorithm working on frequency tracking and phasor estimation. In order to test the performance of the two algorithms, some simulations have been made in the Matlab. The Total Vector Error (TVE) is a commonly used performance criteria, and the TVE results of the two algorithms are compared. The TLS algorithm performs better than LS algorithm when the frequencies of all harmonic components are given.
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Real-time system identification using intelligent algorithmsMadkour, A.A.M., Hossain, M. Alamgir, Dahal, Keshav P., Yu, H. January 2004 (has links)
Yes / 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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Real-time power system disturbance identification and its mitigation using an enhanced least squares algorithmManmek, Thip, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2006 (has links)
This thesis proposes, analyses and implements a fast and accurate real-time power system disturbances identification method based on an enhanced linear least squares algorithm for mitigation and monitoring of various power quality problems such as current harmonics, grid unbalances and voltage dips. The enhanced algorithm imposes less real-time computational burden on processing the system and is thus called ???efficient least squares algorithm???. The proposed efficient least squares algorithm does not require matrix inversion operation and contains only real numbers. The number of required real-time matrix multiplications is also reduced in the proposed method by pre-performing some of the matrix multiplications to form a constant matrix. The proposed efficient least squares algorithm extracts instantaneous sine and cosine terms of the fundamental and harmonic components by simply multiplying a set of sampled input data by the pre-calculated constant matrix. A power signal processing system based on the proposed efficient least squares algorithm is presented in this thesis. This power signal processing system derives various power system quantities that are used for real-time monitoring and disturbance mitigation. These power system quantities include constituent components, symmetrical components and various power measurements. The properties of the proposed power signal processing system was studied using modelling and practical implementation in a digital signal processor. These studies demonstrated that the proposed method is capable of extracting time varying power system quantities quickly and accurately. The dynamic response time of the proposed method was less than half that of a fundamental cycle. Moreover, the proposed method showed less sensitivity to noise pollution and small variations in fundamental frequency. The performance of the proposed power signal processing system was compared to that of the popular DFT/FFT methods using computer simulations. The simulation results confirmed the superior performance of the proposed method under both transient and steady-state conditions. In order to investigate the practicability of the method, the proposed power signal processing system was applied to two real-life disturbance mitigation applications namely, an active power filter (APF) and a distribution synchronous static compensator (D-STATCOM). The validity and performance of the proposed signal processing system in both disturbance mitigations applications were investigated by simulation and experimental studies. The extensive modelling and experimental studies confirmed that the proposed signal processing system can be used for practical real-time applications which require fast disturbance identification such as mitigation control and power quality monitoring of power systems
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Blind Adaptive Multiuser Detection for DS-CDMA System Based on Sliding Window RLS AlgorithmPan, Wei-Hung 10 September 2004 (has links)
Direct sequence code division multiple access (DS-CDMA) technique is one of the significant multiplexing technologies used in wireless communication services. In the DS-CDMA framework, all users have been assigned distinct signature code sequence to achieve multiple accesses within the same frequency band, and allow signal separating at the receiver. Under multipath fading environment with near-far effect, the current CDMA systems employed the RAKE receiver, to enhance the system performance. It is known that if training data is available the minimum mean squares error (MMSE) multiuser receiver, in which the average power of the receiver output is minimized subject to appropriate constraints, could be obtained by solving directly by the constrained Wiener estimation solution. However, if this is not the case, the blind multiuser receiver is an alternative approach to achieve desired performance closed to the one with the MMSE approach.
In this thesis, based on the max/min criterion, the blind multiuser receiver, with linear constraints, is devised. Here constraint equations are written in parametric forms, which depend on the multipath structure of the signal of interest. Constraint parameters are jointly optimized with the parameters of the linear receiver to obtain the optimal parameters. In consequence, the sliding window linearly constrained RLS (SW-LC-RLS) algorithm is employed to implement the optimal blind receiver, with max/min approach. This new proposed scheme can be used to deal with multiple access interference (MAI) suppression for the environments, in which the narrow band interference (NBI) due to other systems is joined suddenly to the DS-CDMA systems, and having serious near-far effect. Under such circumstance, the channel character due to the NBI and near-far effect will become violent time varying, such that the conventional LC-RLS algorithm as well as LC-LMS algorithms could not perform well. Via computer simulation it confirms that our proposed scheme has better capability for MAI suppression in DS-CDMA systems than other existing schemes, and is more robust against the NBI and near-far problems.
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Real-time power system disturbance identification and its mitigation using an enhanced least squares algorithmManmek, Thip, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2006 (has links)
This thesis proposes, analyses and implements a fast and accurate real-time power system disturbances identification method based on an enhanced linear least squares algorithm for mitigation and monitoring of various power quality problems such as current harmonics, grid unbalances and voltage dips. The enhanced algorithm imposes less real-time computational burden on processing the system and is thus called ???efficient least squares algorithm???. The proposed efficient least squares algorithm does not require matrix inversion operation and contains only real numbers. The number of required real-time matrix multiplications is also reduced in the proposed method by pre-performing some of the matrix multiplications to form a constant matrix. The proposed efficient least squares algorithm extracts instantaneous sine and cosine terms of the fundamental and harmonic components by simply multiplying a set of sampled input data by the pre-calculated constant matrix. A power signal processing system based on the proposed efficient least squares algorithm is presented in this thesis. This power signal processing system derives various power system quantities that are used for real-time monitoring and disturbance mitigation. These power system quantities include constituent components, symmetrical components and various power measurements. The properties of the proposed power signal processing system was studied using modelling and practical implementation in a digital signal processor. These studies demonstrated that the proposed method is capable of extracting time varying power system quantities quickly and accurately. The dynamic response time of the proposed method was less than half that of a fundamental cycle. Moreover, the proposed method showed less sensitivity to noise pollution and small variations in fundamental frequency. The performance of the proposed power signal processing system was compared to that of the popular DFT/FFT methods using computer simulations. The simulation results confirmed the superior performance of the proposed method under both transient and steady-state conditions. In order to investigate the practicability of the method, the proposed power signal processing system was applied to two real-life disturbance mitigation applications namely, an active power filter (APF) and a distribution synchronous static compensator (D-STATCOM). The validity and performance of the proposed signal processing system in both disturbance mitigations applications were investigated by simulation and experimental studies. The extensive modelling and experimental studies confirmed that the proposed signal processing system can be used for practical real-time applications which require fast disturbance identification such as mitigation control and power quality monitoring of power systems
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Méthode numérique d'estimation du mouvement des masses mollesThouzé, Arsène 10 1900 (has links)
L’analyse biomécanique du mouvement humain en utilisant des systèmes optoélectroniques et des marqueurs cutanés considère les segments du corps comme des corps rigides. Cependant, le mouvement des tissus mous par rapport à l'os, c’est à dire les muscles et le tissu adipeux, provoque le déplacement des marqueurs. Ce déplacement est le fait de deux composantes, une composante propre correspondant au mouvement aléatoire de chaque marqueur et une composante à l’unisson provoquant le déplacement commun des marqueurs cutanés lié au mouvement des masses sous-jacentes. Si nombre d’études visent à minimiser ces déplacements, des simulations ont montré que le mouvement des masses molles réduit la dynamique articulaire. Cette observation est faite uniquement par la simulation, car il n'existe pas de méthodes capables de dissocier la cinématique des masses molles de celle de l’os. L’objectif principal de cette thèse consiste à développer une méthode numérique capable de distinguer ces deux cinématiques.
Le premier objectif était d'évaluer une méthode d'optimisation locale pour estimer le mouvement des masses molles par rapport à l’humérus obtenu avec une tige intra-corticale vissée chez trois sujets. Les résultats montrent que l'optimisation locale sous-estime de 50% le déplacement des marqueurs et qu’elle conduit à un classement de marqueurs différents en fonction de leur déplacement. La limite de cette méthode vient du fait qu'elle ne tient pas compte de l’ensemble des composantes du mouvement des tissus mous, notamment la composante en unisson.
Le second objectif était de développer une méthode numérique qui considère toutes les composantes du mouvement des tissus mous. Plus précisément, cette méthode devait fournir une cinématique similaire et une plus grande estimation du déplacement des marqueurs par rapport aux méthodes classiques et dissocier ces composantes. Le membre inférieur est modélisé avec une chaine cinématique de 10 degrés de liberté reconstruite par optimisation globale en utilisant seulement les marqueurs placés sur le pelvis et la face médiale du tibia. L’estimation de la cinématique sans considérer les marqueurs placés sur la cuisse et le mollet permet d'éviter l’influence de leur déplacement sur la reconstruction du modèle cinématique. Cette méthode testée sur 13 sujets lors de sauts a obtenu jusqu’à 2,1 fois plus de déplacement des marqueurs en fonction de la méthode considérée en assurant des cinématiques similaires. Une approche vectorielle a montré que le déplacement des marqueurs est surtout dû à la composante à l’unisson. Une approche matricielle associant l’optimisation locale à la chaine cinématique a montré que les masses molles se déplacent principalement autour de l'axe longitudinal et le long de l'axe antéro-postérieur de l'os.
L'originalité de cette thèse est de dissocier numériquement la cinématique os de celle des masses molles et les composantes de ce mouvement. Les méthodes développées dans cette thèse augmentent les connaissances sur le mouvement des masses molles et permettent d’envisager l’étude de leur effet sur la dynamique articulaire. / Biomechanical analysis of human movement using optoelectronic system and skin markers considers body segments as rigid bodies. However the soft tissue motion relative to the bone, including muscles, fat mass, results in relative displacement of markers. This displacement is the results of two components, an own component which corresponds to a random motion of each marker and an in-unison component corresponding to the common movement of skin markers resulting from the movement of the underlying wobbling mass. While most studies aim to minimize these displacements, computer simulation models have shown that the movement of the soft tissue motion relative to the bones reduces the joint kinetics. This observation is only available using computer simulations because there are no methods able to distinguish the kinematics of wobbling mass of the bones kinematics. The main objective of this thesis is to develop a numerical method able to distinguish this different kinematics.
The first aim of this thesis was to assess a local optimisation method for estimating the soft tissue motion using intra-cortical pins screwed into the humerus in three subjects. The results show that local optimisation underestimates of 50% the marker displacements. Also it leads to a different marker ranking in terms of displacement. The limit of local optimisation comes from the fact that it does not consider all the components of the soft tissue motion, especially the in-unison component.
The second aim of this thesis was to develop a numerical method that accounts for all the component of the soft tissue motion. More specifically, this method should provide similar kinematics and estimate large marker displacement and distinguish the two components to conventional approaches. The lower limb is modeled using a 10 degree of freedom chain model reconstructed using global optimisation and the markers placed only on the pelvis and the medial face of the shank. The original estimate of joint kinematics without considering the markers placed on the thigh and on the calf avoids the influences of these markers displacement on the kinematic model reconstruction. This method was tested on 13 subjects who performed hopping trials and obtained up to 2.1 times of marker displacement depending the method considered ensuring similar joint-kinematics. A vector approach shown that marker displacements is more induce by the in-unison component. A matrix approach combining the local optimisation and the kinematic model shown that the wobbling mass moves around the longitudinal axis and along the antero-posterior axis of the bone.
The originality of this thesis is to numerically distinguish the bone kinematics from the wobbling mass kinematics and the two components of the soft tissue motion. The methods developed in this thesis increases the knowledge on soft tissue motion and allow future studies to consider their movement in joint kinetics calculation.
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Méthode numérique d'estimation du mouvement des masses mollesThouzé, Arsène 10 1900 (has links)
L’analyse biomécanique du mouvement humain en utilisant des systèmes optoélectroniques et des marqueurs cutanés considère les segments du corps comme des corps rigides. Cependant, le mouvement des tissus mous par rapport à l'os, c’est à dire les muscles et le tissu adipeux, provoque le déplacement des marqueurs. Ce déplacement est le fait de deux composantes, une composante propre correspondant au mouvement aléatoire de chaque marqueur et une composante à l’unisson provoquant le déplacement commun des marqueurs cutanés lié au mouvement des masses sous-jacentes. Si nombre d’études visent à minimiser ces déplacements, des simulations ont montré que le mouvement des masses molles réduit la dynamique articulaire. Cette observation est faite uniquement par la simulation, car il n'existe pas de méthodes capables de dissocier la cinématique des masses molles de celle de l’os. L’objectif principal de cette thèse consiste à développer une méthode numérique capable de distinguer ces deux cinématiques.
Le premier objectif était d'évaluer une méthode d'optimisation locale pour estimer le mouvement des masses molles par rapport à l’humérus obtenu avec une tige intra-corticale vissée chez trois sujets. Les résultats montrent que l'optimisation locale sous-estime de 50% le déplacement des marqueurs et qu’elle conduit à un classement de marqueurs différents en fonction de leur déplacement. La limite de cette méthode vient du fait qu'elle ne tient pas compte de l’ensemble des composantes du mouvement des tissus mous, notamment la composante en unisson.
Le second objectif était de développer une méthode numérique qui considère toutes les composantes du mouvement des tissus mous. Plus précisément, cette méthode devait fournir une cinématique similaire et une plus grande estimation du déplacement des marqueurs par rapport aux méthodes classiques et dissocier ces composantes. Le membre inférieur est modélisé avec une chaine cinématique de 10 degrés de liberté reconstruite par optimisation globale en utilisant seulement les marqueurs placés sur le pelvis et la face médiale du tibia. L’estimation de la cinématique sans considérer les marqueurs placés sur la cuisse et le mollet permet d'éviter l’influence de leur déplacement sur la reconstruction du modèle cinématique. Cette méthode testée sur 13 sujets lors de sauts a obtenu jusqu’à 2,1 fois plus de déplacement des marqueurs en fonction de la méthode considérée en assurant des cinématiques similaires. Une approche vectorielle a montré que le déplacement des marqueurs est surtout dû à la composante à l’unisson. Une approche matricielle associant l’optimisation locale à la chaine cinématique a montré que les masses molles se déplacent principalement autour de l'axe longitudinal et le long de l'axe antéro-postérieur de l'os.
L'originalité de cette thèse est de dissocier numériquement la cinématique os de celle des masses molles et les composantes de ce mouvement. Les méthodes développées dans cette thèse augmentent les connaissances sur le mouvement des masses molles et permettent d’envisager l’étude de leur effet sur la dynamique articulaire. / Biomechanical analysis of human movement using optoelectronic system and skin markers considers body segments as rigid bodies. However the soft tissue motion relative to the bone, including muscles, fat mass, results in relative displacement of markers. This displacement is the results of two components, an own component which corresponds to a random motion of each marker and an in-unison component corresponding to the common movement of skin markers resulting from the movement of the underlying wobbling mass. While most studies aim to minimize these displacements, computer simulation models have shown that the movement of the soft tissue motion relative to the bones reduces the joint kinetics. This observation is only available using computer simulations because there are no methods able to distinguish the kinematics of wobbling mass of the bones kinematics. The main objective of this thesis is to develop a numerical method able to distinguish this different kinematics.
The first aim of this thesis was to assess a local optimisation method for estimating the soft tissue motion using intra-cortical pins screwed into the humerus in three subjects. The results show that local optimisation underestimates of 50% the marker displacements. Also it leads to a different marker ranking in terms of displacement. The limit of local optimisation comes from the fact that it does not consider all the components of the soft tissue motion, especially the in-unison component.
The second aim of this thesis was to develop a numerical method that accounts for all the component of the soft tissue motion. More specifically, this method should provide similar kinematics and estimate large marker displacement and distinguish the two components to conventional approaches. The lower limb is modeled using a 10 degree of freedom chain model reconstructed using global optimisation and the markers placed only on the pelvis and the medial face of the shank. The original estimate of joint kinematics without considering the markers placed on the thigh and on the calf avoids the influences of these markers displacement on the kinematic model reconstruction. This method was tested on 13 subjects who performed hopping trials and obtained up to 2.1 times of marker displacement depending the method considered ensuring similar joint-kinematics. A vector approach shown that marker displacements is more induce by the in-unison component. A matrix approach combining the local optimisation and the kinematic model shown that the wobbling mass moves around the longitudinal axis and along the antero-posterior axis of the bone.
The originality of this thesis is to numerically distinguish the bone kinematics from the wobbling mass kinematics and the two components of the soft tissue motion. The methods developed in this thesis increases the knowledge on soft tissue motion and allow future studies to consider their movement in joint kinetics calculation.
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Low-order coupled map lattices for estimation of wake patterns behind vibrating flexible cablesBalasubramanian, Ganapathi Raman 08 September 2003 (has links)
"Fluid-structure interaction arises in a wide array of technological applications including naval and marine hydrodynamics, civil and wind engineering and flight vehicle aerodynamics. When a fluid flows over a bluff body such as a circular cylinder, the periodic vortex shedding in the wake causes fluctuating lift and drag forces on the body. This phenomenon can lead to fatigue damage of the structure due to large amplitude vibration. It is widely believed that the wake structures behind the structure determine the hydrodynamic forces acting on the structure and control of wake structures can lead to vibration control of the structure. Modeling this complex non-linear interaction requires coupling of the dynamics of the fluid and the structure. In this thesis, however, the vibration of the flexible cylinder is prescribed, and the focus is on modeling the fluid dynamics in its wake. Low-dimensional iterative circle maps have been found to predict the universal dynamics of a two-oscillator system such as the rigid cylinder wake. Coupled map lattice (CML)models that combine a series of low-dimensional circle maps with a diffusion model have previously predicted qualitative features of wake patterns behind freely vibrating cables at low Reynolds number. However, the simple nature of the CML models implies that there will always be unmodelled wake dynamics if a detailed, quantitative comparison is made with laboratory or simulated wake flows. Motivated by a desire to develop an improved CML model, we incorporate self-learning features into a new CML that is trained to precisely estimate wake patterns from target numerical simulations and experimental wake flows. The eventual goal is to have the CML learn from a laboratory flow in real time. A real-time self-learning CML capable of estimating experimental wake patterns could serve as a wake model in a future anticipated feedback control system designed to produce desired wake patterns. A new convective-diffusive map that includes additional wake dynamics is developed. Two different self-learning CML models, each capable of precisely estimating complex wake patterns, have been developed by considering additional dynamics from the convective-diffusive map. The new self-learning CML models use adaptive estimation schemes which seek to precisely estimate target wake patterns from numerical simulations and experiments. In the first self-learning CML, the estimator scheme uses a multi-variable least-squares algorithm to adaptively vary the spanwise velocity distribution in order to minimize the state error (difference between modeled and target wake patterns). The second self-learning model uses radial basis function neural networks as online approximators of the unmodelled dynamics. Additional unmodelled dynamics not present in the first self-learning CML model are considered here. The estimator model uses a combination of a multi-variable normalized least squares scheme and a projection algorithm to adaptively vary the neural network weights. Studies of this approach are conducted using wake patterns from spectral element based NEKTAR simulations of freely vibrating cable wakes at low Reynolds numbers on the order of 100. It is shown that the self-learning models accurately and efficiently estimate the simulated wake patterns within several shedding cycles. Next, experimental wake patterns behind different configurations of rigid cylinders were obtained. The self-learning CML models were then used for off-line estimation of the stored wake patterns. With the eventual goal of incorporating low-order CML models into a wake pattern control system in mind, in a related study control terms were added to the simple CML model in order to drive the wake to the desired target pattern of shedding. Proportional, adaptive proportional and non-linear control techniques were developed and their control efficiencies compared."
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New Techniques for Estimation of Source Parameters : Applications to Airborne Gravity and Pseudo-Gravity Gradient TensorsBeiki, Majid January 2011 (has links)
Gravity gradient tensor (GGT) data contains the second derivatives of the Earth’s gravitational potential in three orthogonal directions. GGT data can be measured either using land, airborne, marine or space platforms. In the last two decades, the applications of GGT data in hydrocarbon exploration, mineral exploration and structural geology have increased considerably. This work focuses on developing new interpretation techniques for GGT data as well as pseudo-gravity gradient tensor (PGGT) derived from measured magnetic field. The applications of developed methods are demonstrated on a GGT data set from the Vredefort impact structure, South Africa and a magnetic data set from the Särna area, west central Sweden. The eigenvectors of the symmetric GGT can be used to estimate the position of the causative body as well as its strike direction. For a given measurement point, the eigenvector corresponding to the maximum eigenvalue points approximately toward the center of mass of the source body. For quasi 2D structures, the strike direction of the source can be estimated from the direction of the eigenvectors corresponding to the smallest eigenvalues. The same properties of GGT are valid for the pseudo-gravity gradient tensor (PGGT) derived from magnetic field data assuming that the magnetization direction is known. The analytic signal concept is applied to GGT data in three dimensions. Three analytic signal functions are introduced along x-, y- and z-directions which are called directional analytic signals. The directional analytic signals are homogenous and satisfy Euler’s homogeneity equation. Euler deconvolution of directional analytic signals can be used to locate causative bodies. The structural index of the gravity field is automatically identified from solving three Euler equations derived from the GGT for a set of data points located within a square window with adjustable size. For 2D causative bodies with geometry striking in the y-direction, the measured gxz and gzz components of GGT can be jointly inverted for estimating the parameters of infinite dike and geological contact models. Once the strike direction of 2D causative body is estimated, the measured components can be transformed into the strike coordinate system. The GGT data within a set of square windows for both infinite dike and geological contact models are deconvolved and the best model is chosen based on the smallest data fit error. / Felaktigt tryckt som Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 730
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Discrete-time Concurrent Learning for System Identification and Applications: Leveraging Memory Usage for Good LearningDjaneye-Boundjou, Ouboti Seydou Eyanaa January 2017 (has links)
No description available.
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