The authors discuss high-voltage power conversion. Conventional series connection and three-level voltage source inverter techniques are reviewed and compared. A novel versatile multilevel commutation cell is introduced: it is shown that this topology is safer and more simple to control, and delivers purer output waveforms. The authors show how this technique can be applied to either choppers or voltage-source inverters and generalized to any number of switches.<<ETX>>

Multi-level conversion : high voltage choppers and voltage-source inverters

Provided is an electric power converter. A First and second series circuits of switching devices and a series circuit of capacitors are connected in parallel. Between the connection point in the first series circuit of switching devices and the connection point in the series circuit of capacitors, a first bidirectional switch is connected and, between the connection point in the second series circuit of switching devices and the connection point in the series circuit of capacitors, a second bidirectional switch is connected. The connection point in the first series circuit of switching devices is connected through a reactor to an input-output common connection line connected to one end of an AC power supply and the other end of the AC power supply is connected to the connection point in the series circuit of capacitors.

Electric power converter

Today, vehicles have been an essential part of our daily life. According to survey, one-third drivers admit they have left their vehicle while it running, which makes the vehicle an easy target for theft. In this paper, we propose a novel driver identification method with wearable device. This approach can be used in continuous authentication to offer a greater degree of multilevel protection. Our proposed method is based on the hypothesis that a driver has a specific habit to drive a vehicle; and such behavioral biometrics can be captured from the wearable device. In order to validating this hypothesis, we have used the wireless sensor modules to collect driver's behavioral information. Then, the experimental results indicate that the proposed approach is feasible.

A novel driver identification method using wearables

We summarize the design and implementation of a laboratory model "the Elevator" and its control. We focus on the hardware and software components and on the process of design, actual implementation and application control. The mentioned model is located at the Technical University in Kosice, Department of Cybernetics and Artificial Intelligence at the Center of Modern Control Techniques and Industrial Informatics. The model is used for education offering the possibility to implement various algorithms and programs in ladder diagrams.

PI control of laboratory model elevator via ladder logic in PLC

Electroencephalogram channel selection based on pearson correlation coefficient for motor imagery-brain-computer interface

/pdf/a-prototype-of-a-fingerprint-based-ignition-systems-in-59mwcpw5l9.pdf

A prototype of a fingerprint based ignition systems in vehicles

Brain computer interface (BCI) is one of the technologies growing at an exponential rate with its applications extended to medical and non-medical fields. EEG is widely used in BCI for detection and analysis of abnormalities of the brain. EEG is characterized by inherently high temporal resolution and precision, low spatial resolution and specificity plus contains artifacts and redundant or noise information both from the subject and equipment interferences. Thus, feature extraction is a critical issue in translation algorithm development for BCI. Above all, BCI still faces a lot challenges that results in performance variation across and even within subjects. Thus, this work provides a concise but all encompassing review of methods that have been adopted in the recent time for development of an EEG classification in BCI.

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EEG Classification in Brain Computer Interface (BCI): A Pragmatic Appraisal

This paper presents a novel two-phase hybrid optimization algorithm called Real Coded Genetic Algorithm Initialized Newton Raphson (GAIN) method for solving the transcendental nonlinear equations characterizing harmonics in multilevel converters. The proposed hybrid Real GAIN method is developed in such a way that Real Coded Genetic Algorithm (RCGA) is the primary optimizer exploiting its global search capabilities by directing the search towards the optimal region, and Newton Raphson method is then employed as a local search method to fine tune the best solution provided by RCGA in each evolution. The proposed method is implemented for the offline computation of the optimum switching angles in an 11-level inverter so that the required fundamental voltage is produced while the low order harmonics specifically the 5, 7, 11 and 13 harmonics which are more harmful and more difficult to remove with filters are eliminated. Computational and MATLAB simulation results clearly demonstrate the effectiveness and high spectral performance of the proposed algorithm. KeywordsMultilevel inverter, Selective Harmonics Elimination (SHE), Real Coded Genetic Algorithm (RCGA), Newton Raphson method INTRODUCTION Multilevel voltage source inverters have recently become very popular in medium and high power applications such as large motor drives and electric utilities due to their ability to meet the increasing demand of power ratings and high power quality. By synthesizing the desired ac output voltage of a multilevel inverter from several levels of dc input voltages, staircase waveforms are produced, which approach the sinusoidal waveform with low harmonic distortion. In comparison with the hardswitched two-level pulse width modulation (PWM) inverters, multilevel inverters have a lower dv/dt per switching, lower electro-magnetic interference (EMI), considerably reduced switching loss and higher efficiency [1, 2]. Due to their high spectral performance and ability to attain a higher voltage with low harmonics without the use of transformers, multilevel inverters have drawn tremendous interest in applications such as industrial motor drives, High Voltage Direct Current (HVDC) transmission, flexible AC transmission system (FACTs) and utility interface for renewable energy systems because several batteries, fuel cells, solar cells, or rectified wind turbines or microturbines can be connected through a multilevel inverter to feed a load or interconnect to the ac grid without voltage balancing problems [1, 2]. Basically, there are three multilevel converter topologies and they are as follows: Diode-Clamped Multilevel Converter (DCMC) which is based on the neutral-point-clamped (NPC) inverter topology introduced by Nabae, et al, in 1981 [3], Capacitor-Clamped Multilevel Converter (CCMC) also known as flying capacitor or multicell converter proposed by Meynard and Foch in 1992 [3], and Cascaded Multicell Converter (CMC) otherwise known as Cascaded H-bridge Multilevel Converter (CHBMLC) [5, 6]. However many varieties of each topology as well as hybrid of the fundamental topologies such as Generalized P2 Converter, Mixed-Level Hybrid Converter, Asymmetric Hybrid converter have been developed but with the same underlying principle [7-11]. Several modulation techniques and control paradigms have been developed for multilevel converters among which are Sinusoidal Pulse Width Modulation (SPWM), Selective Harmonic Elimination (SHE) method, Space Vector Control (SVC), and Space Vector Pulse Width Modulation (SVPWM) [1, 2,]. Selective Harmonics Elimination (SHE) method at fundamental switching frequency arguably gives the best spectral performance. The main challenge associated with the SHE method is how to obtain analytical solutions of the nonlinear transcendental equations that contain trigonometric terms [12]. The traditional methods used for solving this kind of optimization problems include derivativedependent method like Newton Raphson method which is very fast and accurate but risks being trapped at a local optimum and diverges if the arbitrarily chosen initial values are not sufficiently close to the roots [13-16]. Evolutionary algorithms like Ant Colony Optimization (ACO) [17], Particle Swarm Optimization (PSO) [18] and the conventional Binary Coded Genetic Algorithm (BCGA) [19-21] are derivative free and are successful in locating the optimal solution with any arbitrarily chosen initial values, but they are usually slow in convergence and require much computing time. Also, they minimize rather than eliminate the unwanted low order harmonics Chiasson et al [22] proposed a method based on Elimination theory using resultants of polynomials to determine the solutions of the SHE equations. A difficulty with this approach is that as the number of levels increases, the order of the polynomials becomes very high, thereby making the computations of solutions of these polynomial equations very complex. Another approach uses Walsh functions [23-25] where solving linear equations, instead of non-linear transcendental equations, optimizes the switching angle. The method results in a set of algebraic matrix equations and the calculation of the optimal switching angles is a complex and time-consuming operation. 3107 International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 9, September 2013 IJ E R T IJ E R T ISSN: 2278-0181 www.ijert.org IJERTV2IS90907 II. CASCADED H-BRIDGE MULTILEVEL INVERTERS Cascaded H-bridge multilevel converters consist of a number of H-bridge power conditioning cells, each supplied by an isolated source on the DC side and seriesconnected on the AC side [1, 2, 6, 8, 16]. The structure of a single phase cascaded H-bridge multilevel converter is shown in Figure 1. Fig. 1. Configuration of an 11-level single-phase cascaded H-bridge multilevel converter The number of output phase voltage levels in a cascaded H-Bridge inverter is defined by n =2s +1, where s is the number H-bridges per phase connected in cascade. Each H-bridge switch can generate three different voltage levels: + dc V , 0, and dc V by connecting the DC source to the AC output by different combinations of the four switches 1 S , 2 S , 3 S , and 4 S shown in the figure. To obtain + dc V , switches 1 S and 4 S are turned on, whereas – dc V can be obtained by turning on switches 2 S and 3 S . By turning on 1 S and 2 S , or 3 S and 4 S , the output voltage is zero. The outputs of H-bridge switches are connected in series such that the synthesized AC voltage waveform is the summation of all voltages from the cascaded H-bridge cells [22]. III. PROBLEM FORMULATION The Fourier series expansion of the staircase output voltage waveform shown in Figure 2 is expressed in equation (1). Fig. 2. Output voltage waveform of an 11-level cascaded H-bridge multilevel converter using fundamental frequency switching scheme. ) sin( ) ( ) ( t n H t V n     (1)

Selective Harmonic Elimination in Multilevel Inverter Using Real Coded Genetic Algorithm Initialized Newton Raphson Method

In this paper problem of detecting different type of defects on random textured tiles surfaces is addressed. Since Gabor filters allows optimal localization both in the spatial domain and in the spatial-frequency domain it is been utilized in the proposed technique to extract texture features which are useful for detecting defect edges on the tile. Kohonen’s Self-Organizing Maps (SOM) is used for reducing the feature vectors to obtain 1-dimensional feature map (scalar image). The output of the SOM is smoothed with Gaussian filtering mask and Canny’s edge edge-detection method is applied to the smoothed feature map image to obtain the edge map of the detected defect from the tile surface. The results obtained when the proposed technique is tested on various random texture tiles confirm its efficiency.

Novel defect segmentation technique in random textured tiles

The used of DC motor in various applications has been increased due to the ease with which it speed can be controlled to give the desired performance characteristics under various condition. PID controllers are widely used in DC motor speed control due to its simple structure and robustness to the modeling error, however their effectiveness is often limited due to the poor selection (or tuning) of its parameters. To facilitate the determination of the appropriate values of the parameters of the PID controller for the control of DC motor at any set point therefore required using appropriate tuning method. This paper provides a better understanding of how PID controller is tuned using Ziegler-Nichols Step Response, Cohen-Coon Method and Chien–Hrones–Reswick (CHR) method. Experimental results of PID control of DC motor with load coupled by gear shows that CHR-PID tunings gives a much improved performance over Ziegler-Nichols Step Response and Cohen-Coon PID-tuning with settling time of 355sec., 112sec., and 111 sec . respectively at each set point Keywords: DC motor, Ziegler-Nichols Step Response, Cohen-Coon method and CHR method

/pdf/dc-motor-with-load-coupled-by-gears-speed-control-using-445o9wajqj.pdf

David O. Aborisade

Papers

A prototype of a fingerprint based ignition systems in vehicles

EEG Classification in Brain Computer Interface (BCI): A Pragmatic Appraisal

Selective Harmonic Elimination in Multilevel Inverter Using Real Coded Genetic Algorithm Initialized Newton Raphson Method

Novel defect segmentation technique in random textured tiles

DC Motor with Load Coupled by Gears Speed Control using Modified Ziegler-Nichols Based PID Tunings