Using ant colony optimization for routing in microprocesors

Power consumption is an important constraint on VLSI systems. With the advancement in technology, it is now possible to pack a large range of functionalities into VLSI devices. Hence it is important to find out ways to utilize these functionalities with optimized power consumption. This work focuses on curbing power consumption at the design stage. This work emphasizes minimizing active power consumption by minimizing the load capacitance of the chip. Capacitance of wires and vias can be minimized using Ant Colony Optimization (ACO) algorithms. ACO provides a multi agent framework for combinatorial optimization problems and hence is used to handle multiple constraints of minimizing wire-length and vias to achieve the goal of minimizing capacitance and hence power consumption. The ACO developed here is able to achieve an 8% reduction of wire-length and 7% reduction in vias thereby providing a 7% reduction in total capacitance, compared to other state of the art routers

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area

Design and Implementation of Control Techniques of Power Electronic Interfaces for Photovoltaic Power Systems

The aim of this thesis is to scrutinize and develop four state-of-the-art power electronics converter control techniques utilized in various photovoltaic (PV) power conversion schemes accounting for maximum power extraction and efficiency. First, Cascade Proportional and Integral (PI) Controller-Based Robust Model Reference Adaptive Control (MRAC) of a DC-DC boost converter has been designed and investigated. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while operating in continuous conduction mode (CCM). The proposed control scheme efficiently resolved complications and challenges by using features of cascade PI control loop in combination with properties of MRAC. The accuracy of the proposed control system’s ability to track the desired signals and regulate the plant process variables in the most beneficial and optimised way without delay and overshoot is verified. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed two times with considerably improved disturbance rejection. Second, (P)roportional Gain (R)esonant and Gain Scheduled (P)roportional (PR-P) Controller has been designed and investigated. The aim of this controller is to create a variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm. The proposed control scheme resolved the drawbacks of conventional P&O MPPT method associated with the use of constant perturbation size that leads to a poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update best estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in a P&O algorithm that characterizes the overall system learning-based real time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcome the challenges namely, complexity, computational burden, implantation cost and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency.Third, the interleaved buck converter based photovoltaic (PV) emulator current control has been investigated. A proportional-resonant-proportional (PR-P) controller is designed to resolve the drawbacks of conventional PI controllers in terms of phase management which means balancing currents evenly between active phases to avoid thermally stressing and provide optimal ripple cancellation in the presence of parameter uncertainties. The proposed controller shows superior performance in terms of 10 times faster-converging transient response, zero steady-state error with significant reduction in current ripple. Equal load sharing that constitutes the primary concern in multi-phase converters has been achieved with the proposed controller. Implementing of robust control theory involving comprehensive time and frequency domain analysis reveals 13% improvement in the robust stability margin and 12-degree bigger phase toleration with the PR-P controller. Fourth, a symmetrical pole placement Method-based Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller has been designed and investigated. The proposed PR-P controller resolved the issues associated with the use of the PI controller which are tracking repeating control input signal with zero steady-state and mitigating the 3rd order harmonic component injected into the grid for single-phase PV systems. Additionally, the PR-P controller has overcome the drawbacks of frequency detuning in the grid and increase in the magnitude of odd number harmonics in the system that constitute the common concerns in the implementation of conventional PR controller. Moreover, the unprecedented design process based on changing notch filter dynamics with symmetrical pole placement around resonant frequency overcomes the limitations that are essentially complexity and dependency on the precisely modelled system. The verification and validation process of the proposed control schemes has been conducted using MATLAB/Simulink and implementing MATLAB/Simulink/State flow on dSPACE Real-time-interface (RTI) 1007 processor, DS2004 High-Speed A/D and CP4002 Timing and Digital I/O boards

Advances in power quality analysis techniques for electrical machines and drives: a review

The electric machines are the elements most used at an industry level, and they represent the major power consumption of the productive processes. Particularly speaking, among all electric machines, the motors and their drives play a key role since they literally allow the motion interchange in the industrial processes; it could be said that they are the medullar column for moving the rest of the mechanical parts. Hence, their proper operation must be guaranteed in order to raise, as much as possible, their efficiency, and, as consequence, bring out the economic benefits. This review presents a general overview of the reported works that address the efficiency topic in motors and drives and in the power quality of the electric grid. This study speaks about the relationship existing between the motors and drives that induces electric disturbances into the grid, affecting its power quality, and also how these power disturbances present in the electrical network adversely affect, in turn, the motors and drives. In addition, the reported techniques that tackle the detection, classification, and mitigations of power quality disturbances are discussed. Additionally, several works are reviewed in order to present the panorama that show the evolution and advances in the techniques and tendencies in both senses: motors and drives affecting the power source quality and the power quality disturbances affecting the efficiency of motors and drives. A discussion of trends in techniques and future work about power quality analysis from the motors and drives efficiency viewpoint is provided. Finally, some prompts are made about alternative methods that could help in overcome the gaps until now detected in the reported approaches referring to the detection, classification and mitigation of power disturbances with views toward the improvement of the efficiency of motors and drives.Peer ReviewedPostprint (published version

Onduleur quasi-Z-source pour un système de traction de véhicules électriques à sources multiples : contrôle et gestion

Abstract: Power electronics play a fundamental role and help to achieve the new goals of the automobiles in terms of energy economy and environment. The power electronic converters are the key elements which interface their power sources to the drivetrain of the electric vehicle (EV). They contribute to obtaining high efficiency and performance in power systems. However, traditional inverters such as voltage-source, current-source inverters and conventional two-stage inverters present some conceptual limitations. Consequently, many research efforts have been focused on developing new power electronic converters suitable for EVs application. In order to develop and enhance the performance of commercial multiple sources EV, this dissertation aims to select and to control the impedance source inverter and to provide management approaches for multiple sources EV traction system. A concise review of the main existing topologies of impedance source inverters has been presented. That enables to select QZSI (quasi-Z-source inverter) topology as promising architectures with better performance and reliability. The comparative study between the bidirectional conventional two-stage inverter and QZSI for EV applications has been presented. Furthermore, comparative study between different powertrain topologies regarding batteries aging index factors for an off-road EV has been explored. These studies permit to prove that QZSI topology represents a good candidate to be used in multi-source EV system. For improving the performance of QZSI applied to EVs, optimized fractional order PI (FOPI) controllers for QZSI is designed with the ant colony optimization algorithm (ACO-NM) to obtain more suitable aging performance index values for the battery. Moreover, this thesis proposes a hybrid energy storage system (HESS) for EVs to allow an efficient energy use of the battery for a longer distance coverage. Optimized FOPI controller and the finite control set model predictive controller (FCS-MPC) for HESS using bidirectional QZSI is applied for the multi-source EV. The flux-weakening controller has been designed to provide a correct operation with the maximum available torque at any speed within current and voltage limits. Simulation investigations are performed to verify the topologies studied and the efficacity of the proposed controller structure with the bidirectional QZSI. Furthermore, Opal-RT-based real-time simulation has been implemented to validate the effectiveness of the proposed HESS control strategy. The results confirm the EV performance enhancement with the addition of supercapacitors using the proposed control configuration, allowing the efficient use of battery energy with the reduction of root-mean-square value, the mean value, and the standard deviation by 57%, 59%, and 27%, respectively, of battery current compared to the battery-only based inverter.L'électronique de puissance joue un rôle fondamental et contribue à atteindre les nouveaux objectifs de l'automobile en termes d'économie d'énergie et d'environnement. Les convertisseurs d’électroniques de puissance sont considérés comme les éléments clés qui interfacent leurs sources d'alimentation avec la chaîne de traction du véhicule électrique (VE). Ils contribuent à obtenir une efficacité et des performances élevées dans les systèmes électriques. Cependant, les onduleurs traditionnels tels que les onduleurs à source de tension, les onduleurs à source de courant et les onduleurs conventionnels à deux étages qui constituent les onduleurs les plus couramment utilisés, présentent certaines limitations conceptuelles. Par conséquent, de nombreux efforts de recherche se sont concentrés sur le développement de nouveaux convertisseurs d’électroniques de puissance adaptés à l'application aux véhicules électriques. Afin de développer et d'améliorer les performances des VEs à sources multiples commerciales, cette thèse vise à sélectionner, contrôler l'onduleur à source impédante et fournit une approche de gestion pour l'application du système de traction du VE à sources multiples. Une revue concise des principales topologies existantes d'onduleur à source impédante a été présentée. Cela a permis de sélectionner la topologie de l’onduleur quasi-Z-source (QZS) comme architectures prometteuses pouvant être utilisées dans les véhicules électriques, avec de meilleures performances et de fiabilité. L'étude comparative entre l'onduleur bidirectionnel conventionnel à deux étages et de celui à QZS pour les applications du VE a été présentée. En outre, une étude comparative entre différentes topologies de groupes motopropulseurs concernant les facteurs d'indice de vieillissement des batteries pour une application du VE hors route a été explorée. Ces études ont permis de prouver que la topologie de l’onduleur QZS représente une bonne topologie candidate à utiliser dans un système de VE à sources multiples. Pour améliorer les performances de l’onduleur QZS appliquées aux véhicules électriques, des contrôleurs PI d'ordre fractionnaire (PIOF) optimisés pour l’onduleur QZS sont conçus avec l'algorithme de colonies de fourmis afin d'obtenir des valeurs d'indice de performance de vieillissement plus appropriées pour la batterie. De plus, cette thèse propose un système de stockage d'énergie hybride (SSEH) pour le VE afin de permettre une utilisation efficace de l'énergie de la batterie pour une couverture de distance plus longue et une extension de son autonomie. L’optimisation du contrôleur PIOF et du contrôleur par modèle prédictif d'ensemble de contrôle fini (CMP-ECF) pour l’onduleur QZS bidirectionnel a été appliqué au VE à sources multiples avec des approches de gestion appuyées par des règles. Le contrôleur d'affaiblissement de flux magnétique du moteur a été conçu pour fournir un fonctionnement correct avec le couple maximal disponible à n'importe quelle vitesse dans les limites de courant et de tension. Des investigations et des simulations sont effectuées pour vérifier les différentes topologies étudiées et l'efficacité de la structure de contrôleur proposée avec l’onduleur QZS bidirectionnel. De plus, une simulation en temps réel basée sur Opal-RT a été mise en œuvre pour valider l'efficacité de la stratégie de contrôle SSEH proposée. Les résultats confirment l'amélioration des performances du VE avec l'ajout d'un supercondensateur utilisant la configuration du contrôle proposée, permettant une utilisation efficace de l'énergie de la batterie avec une réduction de la valeur moyenne quadratique, de la valeur moyenne et de l'écart type de 57%, 59% et 27%, respectivement, du courant de la batterie par rapport à l'onduleur connecté directement à la batterie

EEG-based brain-computer interfaces using motor-imagery: techniques and challenges.

Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have the potential to become groundbreaking technologies in both clinical and entertainment settings. MI data is generated when a subject imagines the movement of a limb. This paper reviews state-of-the-art signal processing techniques for MI EEG-based BCIs, with a particular focus on the feature extraction, feature selection and classification techniques used. It also summarizes the main applications of EEG-based BCIs, particularly those based on MI data, and finally presents a detailed discussion of the most prevalent challenges impeding the development and commercialization of EEG-based BCIs

Automated optimization of reconfigurable designs

Currently, the optimization of reconfigurable design parameters is typically done manually and often involves substantial amount effort. The main focus of this thesis is to reduce this effort. The designer can focus on the implementation and design correctness, leaving the tools to carry out optimization. To address this, this thesis makes three main contributions. First, we present initial investigation of reconfigurable design optimization with the Machine Learning Optimizer (MLO) algorithm. The algorithm is based on surrogate model technology and particle swarm optimization. By using surrogate models the long hardware generation time is mitigated and automatic optimization is possible. For the first time, to the best of our knowledge, we show how those models can both predict when hardware generation will fail and how well will the design perform. Second, we introduce a new algorithm called Automatic Reconfigurable Design Efficient Global Optimization (ARDEGO), which is based on the Efficient Global Optimization (EGO) algorithm. Compared to MLO, it supports parallelism and uses a simpler optimization loop. As the ARDEGO algorithm uses multiple optimization compute nodes, its optimization speed is greatly improved relative to MLO. Hardware generation time is random in nature, two similar configurations can take vastly different amount of time to generate making parallelization complicated. The novelty is efficient use of the optimization compute nodes achieved through extension of the asynchronous parallel EGO algorithm to constrained problems. Third, we show how results of design synthesis and benchmarking can be reused when a design is ported to a different platform or when its code is revised. This is achieved through the new Auto-Transfer algorithm. A methodology to make the best use of available synthesis and benchmarking results is a novel contribution to design automation of reconfigurable systems.Open Acces

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research