Th.--Méd.--Montpellier, 1912-1913. / Montpellier, 1912-1913, n ° 40.

This thesis is concerned with the development of algorithms for simulation optimization (SO), a special case of stochastic optimization where the objective function can only be evaluated through noisy observations from a simulation. Deterministic techniques, when directly applied to simulation optimization problems fail to converge due to their inability to handle randomness thus requiring sophisticated algorithms. However, many existing algorithms dedicated for simulation optimization often show poor performance on implementation as they require extensive parameter tuning. To overcome these shortfalls with existing SO algorithms, we develop ADALINE, a line search based algorithm that eliminates the need for any user defined parameters. ADALINE is designed to identify a local minimum on continuous and integer ordered feasible sets. ADALINE on a continuous feasible set mimics deterministic line search algorithms, while it iterates between a line search and an enumeration procedure on integer ordered feasible sets in its quest to identify a local minimum. ADALINE improves upon many of the existing SO algorithms by determining the sample size adaptively as a trade-off between the error due to estimation and the optimization error, that is, the algorithm expends simulation effort proportional to the quality of the incumbent solution. We also show that ADALINE converges ``almost surely'' to the set of local minima. Finally, our numerical results suggest that ADALINE converges to a local minimum faster, outperforming other advanced SO algorithms that utilize variable sampling strategies. To demonstrate the performance of our algorithm on a practical problem, we apply ADALINE in solving a surgery rescheduling problem. In the rescheduling problem, the objective is to minimize the cost of disruptions to an existing schedule shared between multiple surgical specialties while accommodating semi-urgent surgeries that require expedited intervention. The disruptions to the schedule are determined using a threshold based heuristic and ADALINE identifies the best threshold levels for various surgical specialties that minimizes the expected total cost of disruption. A comparison of the solutions obtained using a Sample Average Approximation (SAA) approach, and ADALINE is provided. We find that the adaptive sampling strategy in ADALINE identifies a better solution quickly than SAA. / Ph. D.

Great portion of today's industry are <em>Adjustable Speed Drives</em> (<em>ASD's</em>) operated in order to fulfill certain processes. When these processes are critical ones or sensitive to voltage disturbances, that might take place due to inserting high load in an area near to the Point of Common Coupling (<em>PCC</em>) of the process or due to a short term outage, few tens of thousands up to millions of dollars will be lost once such interruptions (voltage sags) take place as a result of the process failure. On the other hand, a distorted voltage waveform at the PCC for some sensitive process might malfunction as a result of the high harmonic content of the voltage waveform. Utilities are required to deliver as pure as possible sinusoidal voltage waveform according to certain limits; thus, they might apply fines against the consumers who are responsible for producing high amounts of current harmonics that affect the voltage wave shape at the <em>PCC</em> in order to force them to improve the consumer's load profile by adding filters at <em>PCC</em> for instance. Utilities are charging the consumers who are drawing power at poor power factor as well. <br /><br /> This thesis presents an <em>ASD</em> retrofitted with a dual-functional piece of hardware connected in series to its <em>DC-link</em> that is capable of handling the previously two mentioned problems. In other words, hardware that is capable of providing <em>voltage sag ride-through</em> during the voltage sag conditions on one side, on the other side, during the normal operating conditions, it is capable to mitigate the harmonic contents of the drawn current by the ASD's rectifier and to improve the power factor. <br /><br /> Survey on voltage sag ride-through for ASD's approaches are presented in the literature has been made. Approaches are classified as the topology utilized; first, topologies that utilizes energy storage elements that store energy to compensate the DC-link voltage with during the voltage sags, second, topologies retrofitting the DC-link itself with additional hardware to compensate the DC-link voltage. The first group is capable to provide voltage compensating during the full outages while the second can't. The presented voltage sag ride-through work of this thesis belongs to the second group. <br /><br /> Boost converter has been used as the hardware to compensate the DC-link voltage because of its simplicity and cheap price. An adaptive linear network (ADALINE) is investigated as the detection system to detect the envelope of the input voltage waveform. Once the envelope of the voltage goes below a certain level, the boost converter is activated to compensate the difference between voltage set point and the actual DC-link voltage. Simulation results supporting the proposed configuration are presented. <br /><br /> A third-harmonic current injection approach is utilized in this work in order to achieve <em>total harmonic distortion</em> (<em>THD</em>) mitigation from 32% to 5. 125% (theoretically). Two third-harmonic current injection networks have been investigated; one utilizes a real resistor, the other utilizes a resistor emulator to reduce the energy dissipated. The proposed controller for the resistor emulator does not require a proportional-integral (PI) controller. <br /><br /> As a result of the common devices between the voltage sag ride-through circuitry and the harmonic mitigation one, they can be integrated together in one circuitry connected in series with the DC-link of the ASD. And hence, the dual functionality of the hardware will be achieved. Simulation results supporting the theoretical results have been presented.

Great portion of today's industry are <em>Adjustable Speed Drives</em> (<em>ASD's</em>) operated in order to fulfill certain processes. When these processes are critical ones or sensitive to voltage disturbances, that might take place due to inserting high load in an area near to the Point of Common Coupling (<em>PCC</em>) of the process or due to a short term outage, few tens of thousands up to millions of dollars will be lost once such interruptions (voltage sags) take place as a result of the process failure. On the other hand, a distorted voltage waveform at the PCC for some sensitive process might malfunction as a result of the high harmonic content of the voltage waveform. Utilities are required to deliver as pure as possible sinusoidal voltage waveform according to certain limits; thus, they might apply fines against the consumers who are responsible for producing high amounts of current harmonics that affect the voltage wave shape at the <em>PCC</em> in order to force them to improve the consumer's load profile by adding filters at <em>PCC</em> for instance. Utilities are charging the consumers who are drawing power at poor power factor as well. <br /><br /> This thesis presents an <em>ASD</em> retrofitted with a dual-functional piece of hardware connected in series to its <em>DC-link</em> that is capable of handling the previously two mentioned problems. In other words, hardware that is capable of providing <em>voltage sag ride-through</em> during the voltage sag conditions on one side, on the other side, during the normal operating conditions, it is capable to mitigate the harmonic contents of the drawn current by the ASD's rectifier and to improve the power factor. <br /><br /> Survey on voltage sag ride-through for ASD's approaches are presented in the literature has been made. Approaches are classified as the topology utilized; first, topologies that utilizes energy storage elements that store energy to compensate the DC-link voltage with during the voltage sags, second, topologies retrofitting the DC-link itself with additional hardware to compensate the DC-link voltage. The first group is capable to provide voltage compensating during the full outages while the second can't. The presented voltage sag ride-through work of this thesis belongs to the second group. <br /><br /> Boost converter has been used as the hardware to compensate the DC-link voltage because of its simplicity and cheap price. An adaptive linear network (ADALINE) is investigated as the detection system to detect the envelope of the input voltage waveform. Once the envelope of the voltage goes below a certain level, the boost converter is activated to compensate the difference between voltage set point and the actual DC-link voltage. Simulation results supporting the proposed configuration are presented. <br /><br /> A third-harmonic current injection approach is utilized in this work in order to achieve <em>total harmonic distortion</em> (<em>THD</em>) mitigation from 32% to 5. 125% (theoretically). Two third-harmonic current injection networks have been investigated; one utilizes a real resistor, the other utilizes a resistor emulator to reduce the energy dissipated. The proposed controller for the resistor emulator does not require a proportional-integral (PI) controller. <br /><br /> As a result of the common devices between the voltage sag ride-through circuitry and the harmonic mitigation one, they can be integrated together in one circuitry connected in series with the DC-link of the ASD. And hence, the dual functionality of the hardware will be achieved. Simulation results supporting the theoretical results have been presented.

Due to development of industries, power factor and harmonic pollution have become serious concerns in the power system. This thesis presents an adaptive linear neuron (ADALINE) - based static synchronous compensator (STATCOM) to cope with power quality issues in the industrial power system. The targeted compensating current of the STATCOM is generated based on the so-called LMS algorithm, thus the compensated system current becomes balanced and active even in reactive, unbalanced or distorted loads. In this thesis, the STATCOM is realized by using a three-level neutral point-clamped (NPC) inverter with the in-phase level-shifted sinusoidal pulse width modulation (IPLSPWM). Theoretical analysis of ADALINE method is detailed and hardware implementation of STATCOM is conducted to validate effectiveness of the proposed approach.

Le travail présenté dans ce mémoire concerne l'élaboration d'une stratégie complète d'identification et de commande neuronale d'un filtre actif parallèle (FAP). L'objectif visé est l'amélioration des performances par rapport aux systèmes classiques de dépollution des installations électriques basse tension. Basée sur l'utilisation des techniques neuromimétiques, notre approche de compensation des harmoniques se fait en trois étapes. Les deux premières étapes identifient respectivement les composantes de la tension et les courants harmoniques à l'aide de réseaux de neurones du type Adaline. La troisième étape injecte les courants harmoniques dans le réseau électrique par un module de commande à base de réseaux de neurones multicouches. Plusieurs architectures neuronales ont été développées et comparées pour chacune des étapes. La structure proposée s'adapte automatiquement aux variations de la charge du réseau et donc aux fluctuations du contenu harmonique des perturbations. Elle permet également la compensation sélective des harmoniques et la correction du facteur de charge. Finalement, ces stratégies ont été validées sur un banc expérimental et leur aptitude à l'intégration matérielle a été testée en simulation.

Le travail présenté dans cette thèse a pour objectif de proposer et d'évaluer les performances de différentes techniques de suppression de bruit impulsif de type asynchrone adaptées aux transmissions sur courants porteurs en lignes (CPL) indoor. En effet, outre les caractéristiques physiques spécifiques à ce type de canal de transmission, le bruit impulsif asynchrone reste la contrainte sévère qui pénalise les systèmes CPL en terme de QoS. Pour remédier aux dégradations dues aux bruits impulsifs asynchrones, les techniques dites de retransmission sont souvent très utilisées. Bien qu'elles soient efficaces, ces techniques de retransmission conduisent à une réduction de débit et à l’introduction de délais de traitement supplémentaires pouvant être critiques pour des applications temps réel. Par ailleurs, plusieurs solutions alternatives sont proposées dans la littérature pour minimiser l'impact du bruit impulsif sur les transmissions CPL. Cependant, le nombre de techniques, qui permettent d'obtenir un bon compromis entre capacité de correction et complexité d'implantation reste faible pour les systèmes CPL. Dans ce contexte, nous proposons dans un premier temps d'utiliser un filtre linéaire adaptatif : le filtre de Widrow, nommé aussi ADALINE (ADAptive LInear NEuron), que nous utilisons comme méthode de débruitage pour les systèmes CPL. Pour améliorer les performances du débruitage effectué à l'aide d'ADALINE, nous proposons d'utiliser un réseau de neurones (RN) non linéaire comme méthode de débruitage. Le réseau de neurones est un bon outil qui est une généralisation de la structure du filtre ADALINE. Dans un deuxième temps, pour améliorer les performances du débruitage par un réseau de neurones, nous proposons un procédé d'annulation du bruit impulsif constitué de deux algorithmes : EMD (Empirical Mode Decomposition) associé à un réseau de neurones de type perceptron multicouches. L'EMD effectue le prétraitement en décomposant le signal bruité en signaux moins complexes et donc plus facilement analysables. Après quoi le réseau de neurones effectue le débruitage. Enfin, nous proposons une méthode d'estimation du bruit impulsif utilisant la méthode GPOF (Generalized Pencil Of Function). L'efficacité des deux méthodes, EMD-RN et la technique utilisant l'algorithme GPOF, est évaluée en utilisant une chaîne de simulation de transmission numérique compatible avec le standard HPAV. / The aim of our thesis is to propose and to evaluate the performances of some asynchronous impulsive noise mitigation techniques for transmission over indoor power lines. Indeed, besides the particular physical properties that characterize this transmission channel type, asynchronous impulsive noise remains the difficult constraint to overcome on power lines communications (PLC). Usually, the impact of asynchronous impulsive disturbances over power lines is partly compensated by means of retransmission mechanisms. However, the main drawbacks of the use of retransmission solutions for impulsive noise mitigation are the bitrate loss and the induced time delays that may be prohibitive for real-time services. Although several other countering strategies are proposed in the literature, only very few of them have a good compromise between correction capability and implementing complexity for PLC systems. In this context, we proposed an adaptive linear filter, the Widrow filter, also known as ADALINE (Adaptive LInear neurons), as a denoising method for PLC systems. To improve the performance of the denoising method using ADALINE, we proposed to use a neural network (NN) as a nonlinear denoising method. The neural network is a good generalization of the ADALINE filter. In a second step, to improve the performances of denoising by NN, we proposed a combined denoising method based on EMD (Empirical Mode Decomposition) and MLPNN (Multi Layer Perceptron Neural Network). The noised signal is pre-processed by EMD which decomposes it into signals less complex and therefore more easily analyzed. Then the MLPNN denoises it. Finally, we proposed an asynchronous impulsive noise estimation method using the GPOF method (Generalized Pencil Of Function). The performances of the two methods, EMD-MLPNN and GPOF technique, are evaluated using a PLC transmission chain compatible with the HPAV standard.

Le travail présenté dans cette thèse a pour objectif de proposer et d'évaluer les performances de différentes techniques de suppression de bruit impulsif de type asynchrone adaptées aux transmissions sur courants porteurs en lignes (CPL) indoor. En effet, outre les caractéristiques physiques spécifiques à ce type de canal de transmission, le bruit impulsif asynchrone reste la contrainte sévère qui pénalise les systèmes CPL en terme de QoS. Pour remédier aux dégradations dues aux bruits impulsifs asynchrones, les techniques dites de retransmission sont souvent très utilisées. Bien qu'elles soient efficaces, ces techniques de retransmission conduisent à une réduction de débit et à l'introduction de délais de traitement supplémentaires pouvant être critiques pour des applications temps réel. Par ailleurs, plusieurs solutions alternatives sont proposées dans la littérature pour minimiser l'impact du bruit impulsif sur les transmissions CPL. Cependant, le nombre de techniques, qui permettent d'obtenir un bon compromis entre capacité de correction et complexité d'implantation reste faible pour les systèmes CPL. Dans ce contexte, nous proposons dans un premier temps d'utiliser un filtre linéaire adaptatif : le filtre de Widrow, nommé aussi ADALINE (ADAptive LInear NEuron), que nous utilisons comme méthode de débruitage pour les systèmes CPL. Pour améliorer les performances du débruitage effectué à l'aide d'ADALINE, nous proposons d'utiliser un réseau de neurones (RN) non linéaire comme méthode de débruitage. Le réseau de neurones est un bon outil qui est une généralisation de la structure du filtre ADALINE. Dans un deuxième temps, pour améliorer les performances du débruitage par un réseau de neurones, nous proposons un procédé d'annulation du bruit impulsif constitué de deux algorithmes : EMD (Empirical Mode Decomposition) associé à un réseau de neurones de type perceptron multicouches. L'EMD effectue le prétraitement en décomposant le signal bruité en signaux moins complexes et donc plus facilement analysables. Après quoi le réseau de neurones effectue le débruitage. Enfin, nous proposons une méthode d'estimation du bruit impulsif utilisant la méthode GPOF (Generalized Pencil Of Function). L'efficacité des deux méthodes, EMD-RN et la technique utilisant l'algorithme GPOF, est évaluée en utilisant une chaîne de simulation de transmission numérique compatible avec le standard HPAV.

Modern methods of speech synthesis are not suitable for restoration of song signals due to lack of vitality and intonation in the resulted sounds. The aim of presented work is to synthesize melismas met in Lithuanian folk songs, by applying Artificial Neural Networks. An analytical survey of rather a widespread literature is presented. First classification and comprehensive discussion of melismas are given. The theory of dynamic systems which will make the basis for studying melismas is presented and finally the relationship for modeling a melisma with nonlinear and dynamic systems is outlined. Investigation of the most widely used Linear Prediction Coding method and possibilities of its improvement. The modification of original Linear Prediction method based on dynamic LPC frame positioning is proposed. On its basis, the new melisma synthesis technique is presented. Developed flexible generalized melisma model, based on two Artificial Neural Networks – a Multilayer Perceptron and Adaline – as well as on two network training algorithms – Levenberg- Marquardt and the Least Squares error minimization – is presented. Moreover, original mathematical models of Fortis, Gruppett, Mordent and Trill are created, fit for synthesizing melismas, and their minimal sizes are proposed. The last chapter concerns experimental investigation, using over 500 melisma records, and corroborates application of the new mathematical models to melisma synthesis of one performer.

Modern methods of speech synthesis are not suitable for restoration of song signals due to lack of vitality and intonation in the resulted sounds. The aim of presented work is to synthesize melismas met in Lithuanian folk songs, by applying Artificial Neural Networks. An analytical survey of rather a widespread literature is presented. First classification and comprehensive discussion of melismas are given. The theory of dynamic systems which will make the basis for studying melismas is presented and finally the relationship for modeling a melisma with nonlinear and dynamic systems is outlined. Investigation of the most widely used Linear Prediction Coding method and possibilities of its improvement. The modification of original Linear Prediction method based on dynamic LPC frame positioning is proposed. On its basis, the new melisma synthesis technique is presented. Developed flexible generalized melisma model, based on two Artificial Neural Networks – a Multilayer Perceptron and Adaline – as well as on two network training algorithms – Levenberg- Marquardt and the Least Squares error minimization – is presented. Moreover, original mathematical models of Fortis, Gruppett, Mordent and Trill are created, fit for synthesizing melismas, and their minimal sizes are proposed. The last chapter concerns experimental investigation, using over 500 melisma records, and corroborates application of the new mathematical models to melisma synthesis of one performer.