Majlesi Journal of Electrical Engineering
Volume:13 Issue: 1, Mar 2019

In this paper a sliding mode control method by use of state feedback on a permanent magnet synchronous generator (PMSG) is proposed. This system by lyapunov exponents known as chaotic system with unstable equilibrium points. Stability of this system with proposed controller is proved by lyapunov theory. Finally, the simulation results shows that mentioned controller converge chaotic system to zero and also the controller is capable of tracking any desired point.

Proliferation of electronics is a major breakthrough in the industrial sector as these play a very promising role in the functioning of the electric machines and together described as an electric drive. The important question here is about the efficiency of the electric drive. Based on this aspect many electric machines have been invented and among all those machines switched reluctance motor (SRM) is said to be more beneficial because of its reduced losses. This paper presents different unconventional converters which are helpful for the functioning of low power SRM drives. Three different converters along with simulation results are presented and based upon the results of the three converters the efficient converter for low power SRM drives is chosen for the hardware development. Testing shows that the proposed converter results are closely correlated with the simulated results.

The aim of this paper is to provide an insight on developing a control strategy for a standalone wind energy conversion system (SWECS) intended to power a dc load. The system mainly consist of wind turbine (WT), generator, power electronics devices, battery bank and its charging control circuit along with pitch angle control of wind turbine. Charging of battery is attained through tip-speed ratio (TSR) MPPT logic. Dc-dc converter acts as charge controller which charges the battery in controlled way. Pitch angle control mechanism generate appropriate pitch angle command to dampen the rotational speed of the wind turbine. It limits the turbine output power, generator speed and rectifier output voltage during high wind speed ensuring electrical and mechanical safety of the wind turbine. The three-phase self- excited induction generator (SEIG) coupled to a wind turbine is used to produce electrical power. It is connected to load via ac-dc-dc converter to obtain regulated voltage at the load side. The efficacy of control logic developed for proposed wind energy conversion system is tested in MATLAB/Simulink platform under varying wind and load profile.

Electric Vehicles (EV) are becoming more popular due to environmental friendly approach. However, due to the dominance of fossil fuel-based conventional vehicle on road, emission reduction is a crucial task. In spite of continuous efforts to keep emission under control with alternative fuels, emissions are not under control. Conversion of Conventional Vehicle (CV) into Plug-In Hybrid Electric Vehicle (PHEV) is a promising solution to keep emissions under control of present vehicles running on the road as per norms. However, performance is limited by the size of an electric powertrain. Size of electric powertrain and its control strategy decided the fuel economy and emissions of vehicle i.e. the right size of the powertrain components is essential to fully exploit the benefits of the hybridization. The trend of electric powertrain design is from driving cycle. This will give better performance at that particular route only. Hence values are misleading for any other route and this design value can’t be generalized. The paper provides driving cycle independent generalized tool for the design of electric drivetrain during conversion of the conventional vehicle into the plug-in hybrid electric vehicle by fundamental force analogy method to get better performance of the vehicle. The MATLAB-Simulink tool is developed to size electric drivetrain parameters. The design parameters can be given as input which will size the electric powertrain i.e. size of motor and battery. In addition, the tool can be used to size battery of new PHEV. The results obtained confirm the effectiveness of proposed tool and compared with designed values of the vehicle. The size of electric powertrain can be utilized as early stage design during conversion of the conventional vehicle into the plug-in hybrid electric vehicle.

The hexagonal shaped slotted Wine glass shaped Co Planar Waveguide (CPW) fed antenna for wireless applications is proposed in this paper. The Woodpile based Electronic Bandgap (EBG) structure is used as linked ground surface for bandwidth and gain enhancement. The performance characteristics of different sized strip widths of woodpile structures with wine glass shaped antenna are carried out. The antenna resonates in the band of 2 GHz, 5 GHz and 7 GHz. The band width enhancement of 43 % and gain of 9 dB at 1.9910 GHz for 1mm strip width of woodpile is observed. The group delay variation and E –plane co and cross polarization radiation patterns are also obtained for various strip widths of woodpile structure. The group delay is maintained less than 5 ns and there is significant difference between co and cross polarization for E- plane radiation patterns for 1mm strip width of woodpile structure. The antenna is fabricated with hexagonal slot and 1mm strip width woodpile structure and tested for return loss and radiation pattern.

Doubly fed induction generator (DFIG) is one of the most popular generators used nowadays in wind turbine systems (WTSs). This machine has some interesting advantages especially in variables speed applications. In the DFIG-based WTS, the rotor side of the machine is normally fed by a two-level power inverter controlled by the usual pulse width modulation (PWM) technique. This last has a principal disadvantages which is the high level of harmonic distortion. In this paper, we propose a novel technique based on space vector modulation (SVM) and fuzzy logic in order to performs the power provided by the DFIG to the grid. Simulation results show the efficiency of the proposed technique especially on the quality of the provided power comparatively to the usual PWM

Epilepsy is a neurological disorder occurs at the central nervous system, Electroencephalography (EEG) is the reliable tool for analyzing the human brain activity with the help of the signals, and moreover, it plays a significant role in the detection of epileptic seizures. The abnormal electrical discharge leads to loss of memory, from the recent survey over five crore people are affected by epilepsy. An effective detection system is a vital solution for detecting the epileptic disease in the initial stage. In this paper, an improved epilepsy seizure detecting system is improved with better accuracy. We proposed EEG signal in both time and frequency domain with the use of Discrete Stationary wavelet-based Stockwell transform (DSWST), the feature extraction is processed by a temporal feature, spectral feature and Amplitude Distribution Estimation (ADE) from EEG signals in which the normal EEG signals will have various spectral and temporal centroids. Also, a modified filter bank based particle swarm optimization (MF-PSO) helps for the feature selection; it significantly improves the classifier accuracy. Finally, a Hybrid K nearest support vector machine (Kn-SVM) is employed for classification to investigate the performance of feature to classify the brain signals into three groups of normal (healthy), seizure free (inter-ictal) and during a seizure (ictal) groups.

This paper present the predictive control based speed, flux and torque prediction of a double stator induction motor. We performed first, the model of the DSIM as well as the direct vector control. We adopted the classical PI controllers for the speed control, the flux, and thus for setting the stator’s currents. In order to minimize the transient control and reduce the impact of measurement noise on the control signal, we used the multivariable generalized predictive control instead the vector control, which must require a flux and torque estimation. The results show, the effectiveness of the proposed method especially in the parameters variation and/or the change of the reference speed.

In this paper, a model reference adaptive controller (MRAC) with a RST control structure is employed to control the depth of the anesthesia. The polynomial coefficients of the RST controller are adjusted according to a fractional order normalized gradient based adaptation mechanism. The propofol infusion rate and the Bispectral Index (BIS) are considered as the system input and output, respectively. The propofol distribution in the patient model is described with a Pharmacokinetic-Pharmacodynamic (PK-PD) model. The PK-PD model parameters depend on physical specifications of the patient like age, weight, and gender. The proposed MRAC is employed to reach the desired BIS in the presence of disturbance and the measurement noise for different patients. Simulation results demonstrate the effectiveness of the proposed method.

This outcome of this research paper improves the quality and performance of the power system by using a four-quadrant chopper circuit in the DC –LINK of the variable speed drive systems (VSDS). In addition, the effects on reducing the ripple factor for both the current and voltage in DC-LINK are illustrated. In this study, a variable speed drive system is simulated and designed with the proposed chopper. Furthermore, the control system of pulses for the transistors is determined. Finally, a discussion of the results is introduced. The given results show the advantages of using the proposed chopper circuit with variable speed drive systems. Likewise, the superiority of the proposed method over other newly suggested techniques is verified by several simulation scenarios.

The necessity to tackle the increasing common concern about safety issues, urges the scientific community to come up with the development of innovative intruder detection and early warning security systems. One of the most effective technological solutions is provided by the application of WSNs. In this endeavor, most solutions have already adopted supercomputers and other computer resource systems to process the enormous amount of data. Alternatively to this approach, simpler and more easily implementable solutions, such as the WSNmod method (previously published by our research group), are already being put to use. In particular, WSNmod is based on three key elements, the categorization of sensor inputs, the quantization of the inputs and a time-window processing. WSNmod was introduced as an advanced intrusion detection system that focused on the minimization of the false positive alerts. Building on the idea of WSNmod, in this paper we focus, identify and quantify measurable parameters that influence the detection reliability. In addition, the very promising test results of the method and the security system are presented in a range of environmental conditions.

The present day electrical power system is highly complex due to the increase in load demand and distributed generations. Further, the intermittent renewable sources and non-linear power electronic loads connected to the grid deteriorates the power quality of the system. Also, the more and more DC loads like LED lights to save energy consumption are connected to the AC distribution system. These issues can be effectively addressed using the smart micro-grid system. In an individual AC or DC micro-grid, the higher number of AC-DC-AC/DC-AC-DC power conversion stages lead to the increased power losses. Therefore, in this paper, an AC-DC hybrid micro-grid topology is proposed, wherein, AC sources and AC loads are connected to AC grid while DC sources and DC loads are connected to DC grid there by reducing the power conversion losses. The shunt active power filter based 3-phase 4-leg bidirectional interlinking converter using d-q reference current method with PI control is proposed to accomplish the inverter-based & rectifier-based power exchange between AC & DC sub-grids with harmonic current compensation under various grid and load conditions. The analysis is carried out in MATLAB/SIMULINK and results proving the improved power quality.

The WiFi offloading has emerged as a solution to mitigate the surge of traffic in cellular networks. The design of WiFi networks and the placement of Access Points (APs) has a considerable impact on the overall performance and the corresponding capital and operational expenditure (CAPEX/OPEX). Therefore, the minimum required number of APs without severe performance degradation is one of the challenges in WiFi offloading. In this paper, we investigate the impact of multi-rate WiFi APs on the offloading performance. A numerical analysis is presented to compare the minimum required number of APs in two modes of single-rate and multi-rate of IEEE 802.11 WLAN. The analysis results indicate the privilege of multi-rate WiFi AP when compared to single-rate WiFi AP. Moreover, the evaluation results show that required WiFi APs in multi-rate are 30% less than single rate WiFi APs.