New control algorithm for single-phase series active power filter

This paper presents a single-phase Series Active Power Filter (Series APF) for mitigation of the load voltage harmonic content, while maintaining the voltage on the DC side regulated without the support of a voltage source. The proposed series active power filter control algorithm eliminates the additional voltage source to regulate the DC voltage, and with the adopted topology it is not used a coupling transformer to interface the series active power filter with the electrical power grid. The paper describes the control strategy which encapsulates the grid synchronization scheme, the compensation voltage calculation, the damping algorithm and the dead-time compensation. The topology and control strategy of the series active power filter have been evaluated in simulation software and simulations results are presented. Experimental results, obtained with a developed laboratorial prototype, validate the theoretical assumptions, and are within the harmonic spectrum limits imposed by the international recommendations of the IEEE-519 Standard.

Mechanistic insights into cytosolic molecular chaperones in protein unfolding and disaggregation

Under optimal non-physiological conditions of low concentrations and low temperatures, proteins may spontaneously fold to the native state, as all the information for folding lies in the amino acid sequence of the polypeptide. However, under conditions of stress or high protein crowding as inside cells, a polypeptide may misfold and enter an aggregation pathway resulting in the formation of misfolded conformers and fibrils, which can be toxic and lead to neurodegenerative illnesses, such as Alzheimer's, Parkinson's or Huntington's diseases and aging in general. To avert and revert protein misfolding and aggregation, cells have evolved a set of proteins called molecular chaperones. Here, I focussed on the human cytosolic chaperones Hsp70 (DnaK) and HspllO, and co-chaperone Hsp40 (DnaJ), and the chaperonin CCT (GroEL). The cytosolic molecular chaperones Hsp70s/Hspll0s and the chaperonins are highly upregulated in bacterial and human cells under different stresses and are involved both in the prevention and the reversion of protein misfolding and aggregation. Hsp70 works in collaboration with Hsp40 to reactivate misfolded or aggregated proteins in a strict ATP dependent manner. Chaperonins (CCT and GroEL) also unfold and reactivate stably misfolded proteins but we found that it needed to use the energy of ATP hydrolysis in order to evict over- sticky misfolded intermediates that inhibited the unfoldase catalytic sites. Ill In this study, we initially characterized a particular type of inactive misfolded monomeric luciferase and rhodanese species that were obtained by repeated cycles of freeze-thawing (FT). These stable misfolded monomeric conformers (FT-luciferase and FT-rhodanese) had exposed hydrophobic residues and were enriched with wrong ß-sheet structures (Chapter 2). Using FT-luciferase as substrate, we found that the Hsp70 orthologs, called HspllO (Sse in yeast), acted similarly to Hsp70 as were bona fide ATP- fuelled polypeptide unfoldases and was much more than a mere nucleotide exchange factor, as generally thought. Moreover, we found that HspllO collaborated with Hsp70 in the disaggregation of stable protein aggregates in which Hsp70 and HspllO acted as equal partners that synergistically combined their individual ATP-consuming polypeptide unfoldase activities to reactivate the misfolded/aggregated proteins (Chapter 3). Using FT-rhodanese as substrate, we found that chaperonins (GroEL and CCT) could catalytically reactivate misfolded rhodanese monomers in the absence of ATP. Also, our results suggested that encaging of an unfolding polypeptide inside the GroEL cavity under a GroES cap was not an obligatory step as generally thought (Chapter 4). Further, we investigated the role of Hsp40, a J-protein co-chaperone of Hsp70, in targeting misfolded polypeptides substrates onto Hsp70 for unfolding. We found that even a large excess of monomeric unfolded a-synuclein did not inhibit DnaJ, whereas, in contrast, stable misfolded a-synuclein oligomers strongly inhibited the DnaK-mediated chaperone reaction by way of sequestering the DnaJ co-chaperone. This work revealed that DnaJ could specifically distinguish, and bind potentially toxic stably aggregated species, such as soluble a-synuclein oligomers involved in Parkinson's disease, and with the help of DnaK and ATP convert them into from harmless natively unfolded a-synuclein monomers (chapter 5). Finally, our meta-analysis of microarray data of plant and animal tissues treated with various chemicals and abiotic stresses, revealed possible co-expressions between core chaperone machineries and their co-chaperone regulators. It clearly showed that protein misfolding in the cytosol elicits a different response, consisting of upregulating the synthesis mainly of cytosolic chaperones, from protein misfolding in the endoplasmic reticulum (ER) that elicited a typical unfolded protein response (UPR), consisting of upregulating the synthesis mainly of ER chaperones. We proposed that drugs that best mimicked heat or UPR stress at increasing the chaperone load in the cytoplasm or ER respectively, may prove effective at combating protein misfolding diseases and aging (Chapter 6).  - Dans les conditions optimales de basse concentration et de basse température, les protéines vont spontanément adopter un repliement natif car toutes les informations nécessaires se trouvent dans la séquence des acides aminés du polypeptide. En revanche, dans des conditions de stress ou de forte concentration des protéines comme à l'intérieur d'une cellule, un polypeptide peu mal se replier et entrer dans un processus d'agrégation conduisant à la formation de conformères et de fibrilles qui peuvent être toxiques et causer des maladies neurodégénératives comme la maladie d'Alzheimer, la maladie de Parkinson ou la chorée de Huntington. Afin d'empêcher ou de rectifier le mauvais repliement des protéines, les cellules ont développé des protéines appelées chaperonnes. Dans ce travail, je me suis intéressé aux chaperonnes cytosoliques Hsp70 (DnaK) et HspllO, la co-chaperones Hsp40 (DnaJ), le complexe CCT/TRiC et GroEL. Chez les bactéries et les humains, les chaperonnes cytosoliques Hsp70s/Hspl 10s et les « chaperonines» sont fortement activées par différentes conditions de stress et sont toutes impliquées dans la prévention et la correction du mauvais repliement des protéines et de leur agrégation. Hsp70 collabore avec Hsp40 pour réactiver les protéines agrégées ou mal repliées et leur action nécessite de 1ATP. Les chaperonines (GroEL) déplient et réactivent aussi les protéines mal repliées de façon stable mais nous avons trouvé qu'elles utilisent l'ATP pour libérer les intermédiaires collant et mal repliés du site catalytique de dépliage. Nous avons initialement caractérisé un type particulier de formes stables de luciférase et de rhodanese monomériques mal repliées obtenues après plusieurs cycles de congélation / décongélation répétés (FT). Ces monomères exposaient des résidus hydrophobiques et étaient plus riches en feuillets ß anormaux. Ils pouvaient cependant être réactivés par les chaperonnes Hsp70+Hsp40 (DnaK+DnaJ) et de l'ATP, ou par Hsp60 (GroEL) sans ATP (Chapitre 2). En utilisant la FT-Luciferase comme substrat nous avons trouvé que HspllO (un orthologue de Hsp70) était une authentique dépliase, dépendante strictement de l'ATP. De plus, nous avons trouvé que HspllO collaborait avec Hsp70 dans la désagrégation d'agrégats stables de protéines en combinant leurs activités dépliase consommatrice d'ATP (Chapitre 3). En utilisant la FT-rhodanese, nous avons trouvé que les chaperonines (GroEL et CCT) pouvaient réactiver catalytiquement des monomères mal repliés en absence d'ATP. Nos résultats suggérèrent également que la capture d'un polypeptide en cours de dépliement dans la cavité de GroEL et sous un couvercle du complexe GroES ne serait pas une étape obligatoire du mécanisme, comme il est communément accepté dans la littérature (Chapitre 4). De plus, nous avons étudié le rôle de Hsp40, une co-chaperones de Hsp70, dans l'adressage de substrats polypeptidiques mal repliés vers Hsp70. Ce travail a révélé que DnaJ pouvait différencier et lier des polypeptide mal repliés (toxiques), comme des oligomères d'a-synucléine dans la maladie de Parkinson, et clairement les différencier des monomères inoffensifs d'a-synucléine (Chapitre 5). Finalement une méta-analyse de données de microarrays de tissus végétaux et animaux traités avec différents stress chimiques et abiotiques a révélé une possible co-expression de la machinerie des chaperonnes et des régulateurs de co- chaperonne. Cette meta-analyse montre aussi clairement que le mauvais repliement des protéines dans le cytosol entraîne la synthèse de chaperonnes principalement cytosoliques alors que le mauvais repliement de protéines dans le réticulum endoplasmique (ER) entraine une réponse typique de dépliement (UPR) qui consiste principalement en la synthèse de chaperonnes localisées dans l'ER. Nous émettons l'hypothèse que les drogues qui reproduisent le mieux les stress de chaleur ou les stress UPR pourraient se montrer efficaces dans la lutte contre le mauvais repliement des protéines et le vieillissement (Chapitre 6).

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Decentralized load balancing for highly irregular search problems

In this paper, we present a distributed computing framework for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available. The framework is based on a peer-to-peer computing environment and dynamic load balancing. The system allows for dynamic resource aggregation, does not depend on any specific meta-computing middleware and is suitable for large-scale, multi-domain, heterogeneous environments, such as computational Grids. Dynamic load balancing policies based on global statistics are known to provide optimal load balancing performance, while randomized techniques provide high scalability. The proposed method combines both advantages and adopts distributed job-pools and a randomized polling technique. The framework has been successfully adopted in a parallel search algorithm for subgraph mining and evaluated on a molecular compounds dataset. The parallel application has shown good calability and close-to linear speedup in a distributed network of workstations.

Dynamic load balancing in parallel KD-tree k-means

One among the most influential and popular data mining methods is the k-Means algorithm for cluster analysis. Techniques for improving the efficiency of k-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting geometrical constraints and an efficient data structure, notably a multidimensional binary search tree (KD-Tree). These techniques allow to reduce the number of distance computations the algorithm performs at each iteration. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient k-Means variants in parallel computing environments. In this work, we provide a parallel formulation of the KD-Tree based k-Means algorithm for distributed memory systems and address its load balancing issue. Three solutions have been developed and tested. Two approaches are based on a static partitioning of the data set and a third solution incorporates a dynamic load balancing policy.

Linear predicted two-pass hexagonal algorithm with parallel implementation for motion estimation

This paper presents a paralleled Two-Pass Hexagonal (TPA) algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for motion estimation. In the TPA., Motion Vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of Macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance or the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.

Paralelled Two-Pass Hexagonal algorithm for motion estimation

This paper presents a paralleled Two-Pass Hexagonal (TPA) algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for motion estimation. In the TPA, Motion Vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of Macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.

Two-pass hexagonal algorithm with parallel implementation for video coding

This paper presents a paralleled Two-Pass Hexagonal (TPA) algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for motion estimation. In the TPA, Motion Vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of Macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.

Adaptive recursive control of a soil testing load frame

Recursive Learning Control (RLC) has the potential to significantly reduce the tracking error in many repetitive trajectory applications. This paper presents an application of RLC to a soil testing load frame where non-adaptive techniques struggle with the highly nonlinear nature of soil. The main purpose of the controller is to apply a sinusoidal force reference trajectory on a soil sample with a high degree of accuracy and repeatability. The controller uses a feedforward control structure, recursive least squares adaptation algorithm and RLC to compensate for periodic errors. Tracking error is reduced and stability is maintained across various soil sample responses.

A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.

Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function

In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

A Cellular Automaton Approach to Spatial Electric Load Forecasting

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)