https://fisica.cab.cnea.gov.ar/gpgpu/images/charlas/medical_image_processing_on_the_gpu.pdf

Medical Image Processing on the GPU : Past, Present and Future

This study presents a new topology of switched-capacitor (SC) multilevel inverter, which is able to step-up input DC voltage to a multilevel AC waveform. This single source inverter is designed based on series connection of the capacitors that charged by input DC sources through a SC network. The proposed modular inverter uses famous T and cross-connected modules that can be simply extended to higher output voltages without increasing the amount of total standing voltage and peak inverse voltage of switches. It generates positive and negative voltage levels inherently, which eliminates requirements of H-bridge inverters that are traditionally used to achieve a bipolar output voltage. Analysis shows that the voltage stress on components, cost, efficiency and losses are kept in acceptable range especially for higher-voltage levels. Capacitor's voltage self-balancing is another inherent advantage of this modular topology which leads to simplify control strategy and eliminate excess balancing circuit. Performance of a six-step proposed structure is evaluated by theoretical analysis, simulation and experimental results.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-pel.2017.0378

Multi-level inverter with combined T-type and cross-connected modules

Most of the complex research problems can be formulated as optimization problems. Emergence of big data technologies have also commenced the generation of complex optimization problems with large size. The high computational cost of these problems has rendered the development of optimization algorithms with parallelization. Particle swarm optimization (PSO) algorithm is one of the most popular swarm intelligence-based algorithm, which is enriched with robustness, simplicity and global search capabilities. However, one of the major hindrance with PSO is its susceptibility of getting entrapped in local optima and; alike other evolutionary algorithms the performance of PSO gets deteriorated as soon as the dimension of the problem increases. Hence, several efforts are made to enhance its performance that includes the parallelization of PSO. The basic architecture of PSO inherits a natural parallelism, and receptiveness of fast processing machines has made this task pretty convenient. Therefore, parallelized PSO (PPSO) has emerged as a well-accepted algorithm by the research community. Several studies have been performed on parallelizing PSO algorithm so far. Proposed work presents a comprehensive and systematic survey of the studies on PPSO algorithms and variants along with their parallelization strategies and applications.

A Survey on Parallel Particle Swarm Optimization Algorithms

The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological behaviour of bird flocks searching for food sources. In this nature-based algorithm, individuals are referred to as particles and fly through the search space seeking for the global best position that minimises (or maximises) a given problem. Today, PSO is one of the most well-known and widely used swarm intelligence algorithms and metaheuristic techniques, because of its simplicity and ability to be used in a wide range of applications. However, in-depth studies of the algorithm have led to the detection and identification of a number of problems with it, especially convergence problems and performance issues. Consequently, a myriad of variants, enhancements and extensions to the original version of the algorithm, developed and introduced in the mid-1990s, have been proposed, especially in the last two decades. In this article, a systematic literature review about those variants and improvements is made, which also covers the hybridisation and parallelisation of the algorithm and its extensions to other classes of optimisation problems, taking into consideration the most important ones. These approaches and improvements are appropriately summarised, organised and presented, in order to allow and facilitate the identification of the most appropriate PSO variant for a particular application.

/pdf/particle-swarm-optimisation-a-historical-review-up-to-the-51fhh4iz76.pdf

Particle Swarm Optimisation: A Historical Review Up to the Current Developments

Assessment of wind energy potential and the economics of wind power generation in Jos, Plateau State, Nigeria

Particle swarm optimization (PSO) is a swarm intelligence algorithm, has been successfully applied to many engineering optimization problems and shown its high search speed in these applications. However, as the dimension and the number of local optima of optimization problems increase, PSO and most existing improved PSO algorithms such as, the standard particle swarm optimization (SPSO) and the Gaussian particle swarm optimization (GPSO), are easily trapped in local optima. In this paper we proposed a novel algorithm based on SPSO called Euclidean particle swarm optimization (EPSO) which has greatly improved the ability of escaping from local optima. To confirm the effectiveness of EPSO, we have employed five benchmark functions to examine it, and compared it with SPSO and GPSO. The experiments results showed that EPSO is significantly better than SPSO and GPSO, especially obvious in higher-dimension problems.

Euclidean Particle Swarm Optimization

DC-DC converters have many applications in the modern world. They provide the required power to the communication backbones, they are used in digital devices like laptops and cell phones, and they have widespread applications in electric cars, to just name a few. DC-DC converters require negative feedback to provide a suitable output voltage or current for the load. Obtaining a stable output voltage or current in presence of disturbances such as: input voltage changes and/or output load changes seems impossible without some form of control. This book tries to train the art of controller design for DC-DC converters. Chapter 1 introduces the DC-DC converters briefly. It is assumed that the reader has the basic knowledge of DC-DC converter (i.e., a basic course in power electronics). The reader learns the disadvantages of open loop control in Chapter 2. Simulation of DC-DC converters with the aid of Simulink® is discussed in this chapter as well. Extracting the dynamic models of DC-DC converters is studied in Chapter 3. We show how MATLAB® and a software named KUCA can be used to do the cumbersome and error-prone process of modeling automatically. Obtaining the transfer functions using PSIM® is studied as well. These days, softwares are an integral part of engineering sciences. Control engineering is not an exception by any means. Keeping this in mind, we design the controllers using MATLAB® in Chapter 4. Finally, references are provided at the end of each chapter to suggest more information for an interested reader. The intended audiences for this book are practice engineers and academians.

Dynamics and Control of DC-DC Converters

https://www.econstor.eu/bitstream/10419/243886/1/1693188082.pdf

Analysis of an LED lighting circuit using a hybrid buck–boost converter with high gain

We have already proposed a ring type switched-capacitor (SC) converter. This converter consists of capacitors which make a ring connection switches. In this paper, we propose programmable converter of DC-DC, DC-AC, AC-DC and AC-AC using a ring type SC converter. The SPICE simulations show that the power efficiency is more than 80%. This converter can provide to some combination of DC or AC input/DC or AC output.

A ring type switched-capacitor (SC) programmable converter with DC or AC input/DC or AC output

For industrial wireless transmitters, a hybrid input charge-pump utilizing thermoelectric energy from waste heat is proposed in this paper. Unlike conventional converters, the proposed capacitor-based converter supplies energy to a wireless transmitter by using a thermoelectric power source in combination with a rechargeable battery source. By combining the battery voltage and the thermoelectric generator (TEG) voltage, the proposed converter achieves a wider input range than conventional converters. Consequently, the proposed converter will enable the development of not only an industrial wireless transmitter but also various clean energy applications. Through theoretical analyses, simulations, and experiments, the following results are shown: 1. Even if the voltage of the TEG is small, the proposed converter can provide the sufficient voltage by compensating the insufficient voltage of the TEG with the battery voltage. 2. The formulas obtained by the theoretical analyses are useful for designing the proposed converter because the theoretical results correspond well with the simulation results. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Kei Eguchi

Papers

Euclidean Particle Swarm Optimization

Dynamics and Control of DC-DC Converters

Analysis of an LED lighting circuit using a hybrid buck–boost converter with high gain

A ring type switched-capacitor (SC) programmable converter with DC or AC input/DC or AC output

A hybrid input charge‐pump using micropower thermoelectric generators