27 research outputs found

    Design and Control of Power Converters 2019

    Get PDF
    In this book, 20 papers focused on different fields of power electronics are gathered. Approximately half of the papers are focused on different control issues and techniques, ranging from the computer-aided design of digital compensators to more specific approaches such as fuzzy or sliding control techniques. The rest of the papers are focused on the design of novel topologies. The fields in which these controls and topologies are applied are varied: MMCs, photovoltaic systems, supercapacitors and traction systems, LEDs, wireless power transfer, etc

    Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals

    Get PDF
    Vibration measurement and monitoring are essential in a wide variety of applications. Vibration measurements are critical for diagnosing industrial machinery malfunctions because they provide information about the condition of the rotating equipment. Vibration analysis is considered the most effective method for predictive maintenance because it is used to troubleshoot instantaneous faults as well as periodic maintenance. Numerous studies conducted in this vein have been published in a variety of outlets. This review documents data-driven and recently published deep learning techniques for vibration-based condition monitoring. Numerous studies were obtained from two reputable indexing databases, Web of Science and Scopus. Following a thorough review, 59 studies were selected for synthesis. The selected studies are then systematically discussed to provide researchers with an in-depth view of deep learning-based fault diagnosis methods based on vibration signals. Additionally, a few remarks regarding future research directions are made, including graph-based neural networks, physics-informed ML, and a transformer convolutional network-based fault diagnosis method

    Intelligent Learning Control System Design Based on Adaptive Dynamic Programming

    Get PDF
    Adaptive dynamic programming (ADP) controller is a powerful neural network based control technique that has been investigated, designed, and tested in a wide range of applications for solving optimal control problems in complex systems. The performance of ADP controller is usually obtained by long training periods because the data usage efficiency is low as it discards the samples once used. Experience replay is a powerful technique showing potential to accelerate the training process of learning and control. However, its existing design can not be directly used for model-free ADP design, because it focuses on the forward temporal difference (TD) information (e.g., state-action pair) between the current time step and the future time step, and will need a model network for future information prediction. Uniform random sampling again used for experience replay, is not an efficient technique to learn. Prioritized experience replay (PER) presents important transitions more frequently and has proven to be efficient in the learning process. In order to solve long training periods of ADP controller, the first goal of this thesis is to avoid the usage of model network or identifier of the system. Specifically, the experience tuple is designed with one step backward state-action information and the TD can be achieved by a previous time step and a current time step. The proposed approach is tested for two case studies: cart-pole and triple-link pendulum balancing tasks. The proposed approach improved the required average trial to succeed by 26.5% for cart-pole and 43% for triple-link. The second goal of this thesis is to integrate the efficient learning capability of PER into ADP. The detailed theoretical analysis is presented in order to verify the stability of the proposed control technique. The proposed approach improved the required average trial to succeed compared to traditional ADP controller by 60.56% for cart-pole and 56.89% for triple-link balancing tasks. The final goal of this thesis is to validate ADP controller in smart grid to improve current control performance of virtual synchronous machine (VSM) at sudden load changes and a single line to ground fault and reduce harmonics in shunt active filters (SAF) during different loading conditions. The ADP controller produced the fastest response time, low overshoot and in general, the best performance in comparison to the traditional current controller. In SAF, ADP controller reduced total harmonic distortion (THD) of the source current by an average of 18.41% compared to a traditional current controller alone

    Electronics for Sensors

    Get PDF
    The aim of this Special Issue is to explore new advanced solutions in electronic systems and interfaces to be employed in sensors, describing best practices, implementations, and applications. The selected papers in particular concern photomultiplier tubes (PMTs) and silicon photomultipliers (SiPMs) interfaces and applications, techniques for monitoring radiation levels, electronics for biomedical applications, design and applications of time-to-digital converters, interfaces for image sensors, and general-purpose theory and topologies for electronic interfaces

    Implantable Micro-Device for Epilepsy Seizure Detection and Subsequent Treatment

    Get PDF
    RÉSUMÉ L’émergence des micro-dispositifs implantables est une voie prometteuse pour le traitement de troubles neurologiques. Ces systĂšmes biomĂ©dicaux ont Ă©tĂ© exploitĂ©s comme traitements non-conventionnels sur des patients chez qui les remĂšdes habituels sont inefficaces. Les rĂ©cents progrĂšs qui ont Ă©tĂ© faits sur les interfaces neuronales directes ont permis aux chercheurs d’analyser l’activitĂ© EEG intracĂ©rĂ©brale (icEEG) en temps rĂ©el pour des fins de traitements. Cette thĂšse prĂ©sente un dispositif implantable Ă  base de microsystĂšmes pouvant capter efficacement des signaux neuronaux, dĂ©tecter des crises d’épilepsie et y apporter un traitement afin de l’arrĂȘter. Les contributions principales prĂ©sentĂ©es ici ont Ă©tĂ© rapportĂ©es dans cinq articles scientifiques, publiĂ©s ou acceptĂ©s pour publication dans les revues IEEE, et plusieurs autres tels que «Low Power Electronics» et «Emerging Technologies in Computing». Le microsystĂšme proposĂ© inclus un circuit intĂ©grĂ© (CI) Ă  faible consommation Ă©nergĂ©tique permettant la dĂ©tection de crises d’épilepsie en temps rĂ©el. Cet CI comporte une prĂ©-amplification initiale et un dĂ©tecteur de crises d’épilepsie. Le prĂ©-amplificateur est constituĂ© d’une nouvelle topologie de stabilisateur d’hacheur rĂ©duisant le bruit et la puissance dissipĂ©e. Les CI fabriquĂ©s ont Ă©tĂ© testĂ©s sur des enregistrements d’icEEG provenant de sept patients Ă©pileptiques rĂ©fractaires au traitement antiĂ©pileptique. Le dĂ©lai moyen de la dĂ©tection d’une crise est de 13,5 secondes, soit avant le dĂ©but des manifestations cliniques Ă©videntes. La consommation totale d’énergie mesurĂ©e de cette puce est de 51 ÎŒW. Un neurostimulateur Ă  boucle fermĂ©e (NSBF), quant Ă  lui, dĂ©tecte automatiquement les crises en se basant sur les signaux icEEG captĂ©s par des Ă©lectrodes intracrĂąniennes et permet une rĂ©troaction par une stimulation Ă©lectrique au mĂȘme endroit afin d’interrompre ces crises. La puce de dĂ©tection de crises et le stimulateur Ă©lectrique Ă  base sur FPGA ont Ă©tĂ© assemblĂ©s Ă  des Ă©lectrodes afin de complĂ©ter la prothĂšse proposĂ©e. Ce NSBF a Ă©tĂ© validĂ© en utilisant des enregistrements d’icEEG de dix patients souffrant d’épilepsie rĂ©fractaire. Les rĂ©sultats rĂ©vĂšlent une performance excellente pour la dĂ©tection prĂ©coce de crises et pour l’auto-dĂ©clenchement subsĂ©quent d’une stimulation Ă©lectrique. La consommation Ă©nergĂ©tique totale du NSBF est de 16 mW. Une autre alternative Ă  la stimulation Ă©lectrique est l’injection locale de mĂ©dicaments, un traitement prometteur de l’épilepsie. Un systĂšme local de livraison de mĂ©dicament basĂ© sur un nouveau dĂ©tecteur asynchrone des crises est prĂ©sentĂ©.----------ABSTRACT Emerging implantable microdevices hold great promise for the treatment of patients with neurological conditions. These biomedical systems have been exploited as unconventional treatment for the conventionally untreatable patients. Recent progress in brain-machine-interface activities has led the researchers to analyze the intracerebral EEG (icEEG) recording in real-time and deliver subsequent treatments. We present in this thesis a long-term safe and reliable low-power microsystem-based implantable device to perform efficient neural signal recording, seizure detection and subsequent treatment for epilepsy. The main contributions presented in this thesis are reported in five journal manuscripts, published or accepted for publication in IEEE Journals, and many others such as Low Power Electronics, and Emerging Technologies in Computing. The proposed microsystem includes a low-power integrated circuit (IC) intended for real-time epileptic seizure detection. This IC integrates a front-end preamplifier and epileptic seizure detector. The preamplifier is based on a new chopper stabilizer topology that reduces noise and power dissipation. The fabricated IC was tested using icEEG recordings from seven patients with drug-resistant epilepsy. The average seizure detection delay was 13.5 sec, well before the onset of clinical manifestations. The measured total power consumption of this chip is 51 ”W. A closed-loop neurostimulator (CLNS) is next introduced, which is dedicated to automatically detect seizure based on icEEG recordings from intracranial electrode contacts and provide an electrical stimulation feedback to the same contacts in order to disrupt these seizures. The seizure detector chip and a dedicated FPGA-based electrical stimulator were assembled together with common recording electrodes to complete the proposed prosthesis. This CLNS was validated offline using recording from ten patients with refractory epilepsy, and showed excellent performance for early detection of seizures and subsequent self-triggering electrical stimulation. Total power consumption of the CLNS is 16 mW. Alternatively, focal drug injection is the promising treatment for epilepsy. A responsive focal drug delivery system based on a new asynchronous seizure detector is also presented. The later system with data-dependent computation reduces up to 49% power consumption compared to the previous synchronous neurostimulator

    Recent Development of Hybrid Renewable Energy Systems

    Get PDF
    Abstract: The use of renewable energies continues to increase. However, the energy obtained from renewable resources is variable over time. The amount of energy produced from the renewable energy sources (RES) over time depends on the meteorological conditions of the region chosen, the season, the relief, etc. So, variable power and nonguaranteed energy produced by renewable sources implies intermittence of the grid. The key lies in supply sources integrated to a hybrid system (HS)

    Computational intelligence techniques for energy storage management

    Get PDF
    Ph. D. ThesisThe proliferation of stochastic renewable energy sources (RES) such as photovoltaic and wind power in the power system has made the balancing of generation and demand challenging for the grid operators. This is further compounded with the liberalization of electricity market and the introduction of real-time electricity pricing (RTP) to reflect the dynamics in generation and demand. Energy storage sources (ESS) are widely seen as one of the keys enabling technology to mitigate this problem. Since ESS is a costly and energy-limited resource, it is economical to provide multiple services using a single ESS. This thesis aims to investigate the operation of a single ESS in a grid-connected microgrid with RES under RTP to provide multiple services. First, artificial neural network is proposed for day-ahead forecasting of the RES, demand and RTP. After the day-ahead forecast is obtained, the day-ahead schedule of energy storage is formulated into a mixed-integer linear programming and implemented in AMPL and solved using CPLEX. This method considers the impact of forecasting errors in the day-ahead scheduling. Empirical evidence shows that the proposed nearoptimal day-ahead scheduling of ESS can achieve a lower operating cost and peak demand. Second, a fuzzy logic-based energy management system (FEMS) for a grid-connected microgrid with RES and ESS is proposed. The objectives of the FEMS are energy arbitrage and peak shaving for the microgrid. These objectives are achieved by controlling the charge and discharge rate of the ESS based on the state-of-charge (SoC) of ESS, the power difference between RES and demand, and RTP. Instead of using a forecasting-based approach, the proposed FEMS is designed with the historical data of the microgrid. It determines the charge and discharge rate of the ESS in a rolling horizon. A comparison with other controllers with the same objectives shows that the proposed controller can operate at a lower cost and reduce the peak demand of the microgrid. Finally, the effectiveness of the FEMS greatly depends on the membership functions. The fuzzy membership functions of the FEMS are optimized offline using a Pareto based multi-objective evolutionary algorithm, nondominated sorting genetic algorithm- II (NSGA-II). The best compromise solution is selected as the final solution and implemented in the fuzzy logic controller. A comparison was made against other control strategies with similar objectives are carried out at a simulation level. Empirical evidence shows that the proposed methodology can find more solutions on the Pareto front in a single run. The proposed FEMS is experimentally validated on a real microgrid in the energy storage test bed at Newcastle University, UK. Furthermore, reserve service is added on top of energy arbitrage and peak shaving to the energy management system (EMS). As such multi-service of a single ESS which benefit the grid operator and consumer is achieved

    Biomedical Engineering

    Get PDF
    Biomedical engineering is currently relatively wide scientific area which has been constantly bringing innovations with an objective to support and improve all areas of medicine such as therapy, diagnostics and rehabilitation. It holds a strong position also in natural and biological sciences. In the terms of application, biomedical engineering is present at almost all technical universities where some of them are targeted for the research and development in this area. The presented book brings chosen outputs and results of research and development tasks, often supported by important world or European framework programs or grant agencies. The knowledge and findings from the area of biomaterials, bioelectronics, bioinformatics, biomedical devices and tools or computer support in the processes of diagnostics and therapy are defined in a way that they bring both basic information to a reader and also specific outputs with a possible further use in research and development

    Méthodes scalables de commande par allocation pour le convertisseur modulaire multiniveaux : de la modélisation à l'implémentation temps réel

    Get PDF
    Dans le cadre de la montĂ©e en puissance des convertisseurs statiques, les diffĂ©rents avantages qu’il y a Ă  utiliser les Convertisseurs Modulaires Multiniveaux (MMC) ont menĂ© Ă  leur popularisation. Cependant, Ă  mesure que le nombre de niveaux de tension et le nombre de phase augmentent, ces convertisseurs prĂ©sentent un nombre de plus en plus important de degrĂ©s de libertĂ© pour en effectuer la commande. Ainsi les MMC reprĂ©sentent un dĂ©fi pour la commande car le nombre de variables de commande est alors supĂ©rieur aux contraintes Ă  satisfaire, faisant d’eux des systĂšmes redondants ou encore sous-dĂ©terminĂ©s ce qui ouvre la voie de l’optimisation. D’abord apparues dans les annĂ©es 1980 dans l’aĂ©ronautique pour tirer profit de la multiplicitĂ© des surfaces aĂ©rodynamiques et des redondances associĂ©es que prĂ©sente un avion afin d’en contrĂŽler sa trajectoire (volets, ailerons, gouvernes
), les mĂ©thodes de commande par allocation ont fait leurs preuves en Ă©tant progressivement appliquĂ©es dans diffĂ©rents domaines technologiques. En parallĂšle ces algorithmes ont fait l’objet de travaux pour amĂ©liorer les performances obtenues et notamment s’adapter aux systĂšmes commandĂ©s. Le sujet de la thĂšse concerne donc le dĂ©veloppement et l’implĂ©mentation en temps rĂ©el de mĂ©thodes de commande par allocation, avec un souci d’optimisation en ligne, pour un systĂšme de conversion d’énergie Ă  base de MMC. La premiĂšre partie de la thĂšse portent sur la modĂ©lisation du convertisseur MMC en vue de sa commande Ă  partir de mĂ©thodes d’allocation. Ce qui implique le dĂ©veloppement de diffĂ©rents modĂšles de commande avec diffĂ©rents niveaux de dĂ©tails et de complexitĂ©. Un rĂ©sultat fort issu de cette premiĂšre partie est un modĂšle de commande dont la complexitĂ© n’est plus influencĂ©e par le nombre de phases du systĂšme Ă©lectrique considĂ©rĂ©. La deuxiĂšme Ă©tape des travaux concerne le dĂ©veloppement d’une nouvelle mĂ©thode d’allocation qui met Ă  profit les avantages des mĂ©thodes prĂ©sentes dans l’état de l’art pour en concevoir une nouvelle plus adaptĂ©e. Ainsi cette dĂ©marche a conduit Ă  la programmation d’un nouvel algorithme d’allocation prĂ©sentant des caractĂ©ristiques dynamiques et statiques rĂ©glables et adaptables simplement, son intĂ©gration aux mĂ©thodes dĂ©jĂ  existantes est aisĂ©e et presque immĂ©diat. La troisiĂšme Ă©tape des travaux combine les travaux prĂ©cĂ©dents. Tout d’abord en simulation, la mĂ©thode de commande par allocation du convertisseur est programmĂ©e puis testĂ©e pour finalement ĂȘtre validĂ©e. Pour la commande diffĂ©rentes architectures sont conçues permettant de rĂ©aliser des comparatifs afin d’évaluer leur capacitĂ© Ă  atteindre les performances requises pour le bon fonctionnement du systĂšme. Il en dĂ©coule une analyse des diffĂ©rents algorithmes de commande proposĂ©s. Le rĂ©sultat principal de cette partie est la conception d’un nouvel algorithme d’allocation permettant de contrĂŽler les tensions aux bornes des condensateurs ainsi que les tous les courants du convertisseur dans chacune des branches et ce indĂ©pendamment du nombre de phases. La quatriĂšme Ă©tape porte sur la validation expĂ©rimentale des mĂ©thodes dĂ©veloppĂ©es. Pour se faire, le convertisseur MMC disponible au laboratoire LAPLACE est utilisĂ© ainsi qu’un ensemble d’outils de prototypage rapide (OPAL-RT) permettant de tester et mettre au point les algorithmes de façon sĂ»re et efficace. La cinquiĂšme partie des travaux concerne l’extension, hors de la zone de fonctionnement nominale du convertisseur, des algorithmes de commande dĂ©veloppĂ©s. En effet une ouverture est proposĂ©e mettant en exergue les capacitĂ©s des mĂ©thodes d’allocation Ă  reconfigurer le fonctionnement du MMC lorsqu’un dĂ©faut apparait dans l’un des sous-modules. Les rĂ©sultats obtenus en simulation montrent une amĂ©lioration de la disponibilitĂ© du convertisseur, c’est-Ă -dire une continuitĂ© de fonctionnement en prĂ©sence de dĂ©fauts ce qui justifie l’intĂ©rĂȘt de poursuivre les travaux dans cette direction
    corecore