Improved Dynamic Response of DC to DC Converter Using Hybrid PSO Tuned Fuzzy Sliding Mode Controller

DC/DC switching converters are widely used in numerous appliances in modern existence. In this paper, the dynamic and transient response of phase shift series resonant DC/DC converter are improved using hybrid particle swarm optimization tuned fuzzy sliding mode controller under starting and load step change conditions. The aim of the control is to regulate the output voltage beneath the load change. The model of the hybrid particle swarm optimization tuned fuzzy sliding mode controller is implemented using Sim Power Systems toolbox of MATLAB SIMULINK. Performance of the proposed dynamic novel control under step load change condition is investigated.

Intensification of Power Quality Using PMSG and Cascaded Multi Cell Trans-Z-Source Inverter

This script depicts the power quality intensification of Wind Energy Transfer System (WETS) using Permanent Magnet Synchronous Generator (PMSG) and Cascaded Multi Cell Trans-Z-Source Inverter (CMCTZSI). The PMSG knocks the induction generator and earlier generators, because of their stimulating performances without taking the frame power. The Trans-Z-Source Inverter with one transformer and one capacitor is connected newly. To increase the boosting ratio gratuity a cascaded impression is proposed with adopting multi-winding transformer which provides an option for this manuscript to use coupled inductor as an alternative of multi-winding transformer and remains the matching voltage gain as cascaded multi cell trans-Z- source inverter. Accordingly the parallel capacitances are also balancing the voltage gain. The parallel correlation of the method is essentially to trim down the voltage stresses and to improve the input current gain of the inverter. By using MALAB Simulation, harmonics can be reduced up to 1.32% and also DC side can be boosted up our required level 200 - 1000 V achievable. The new hardware setup results demonstrate to facilitate the multi cell Trans Z-source inverter. This can be generated high-voltage gain [50 V - 1000 V] and also be credible. Moreover, the level of currents, voltages and Harmonics on the machinery is low.

Intelligence Based Soft Starting Scheme for the Three Phase Squirrel Cage Induction Motor with Extinction Angle AC Voltage Controller

Whenever a squirrel cage induction motor is started, notable electromechanical torque and current pulsations occur. The adverse effects of starting torque pulsations and high inrush current in induction motor are eliminated using digital power electronic soft starting schemes that guarantee higher degrees of compliance of the requirements of an ideal soft starter for the induction motor. Soft starters are cheap, simple, reliable and occupy less volume. In this paper, an experimental setup of soft starting technique with extinction angle AC voltage controller and a speed and stator current based closed loop scheme is demonstrated using Artificial Neural Network (ANN) and Fuzzy Logic Control (FLC) by the way of MATLAB/SIMULINK based simulation. The ANN based soft starting scheme produces best results in terms of smooth starting torque and least inrush current. The results thus obtained were satisfactory and promising.

A Hybrid Particle Swarm Optimization to Forecast Implied Volatility Risk

The application of optimization methods to prediction issues is a continually exploring field.In line with this,this paper investigates the connectedness between the infected cases of COVID-19 and US fear index from a forecasting perspective.The complex characteristics of implied volatility risk index such as non-linearity structure,time-varying and nonstationarity motivate us to apply a nonlinear polynomial Hammerstein model with known structure and unknown parameters.We use the Hybrid Particle Swarm Optimization(HPSO)tool to identify the model parameters of nonlinear polynomial Hammerstein model.Findings indicate that,following a nonlinear polynomial behaviour cascaded to an autoregressive with exogenous input(ARX)behaviour,the fear index in US financial market is significantly affected by COVID-19-infected cases in the US,COVID-19-infected cases in the world and COVID-19-infected cases in China,respectively.Statistical performance indicators provided by the developed models show that COVID-19-infected cases in the US are particularly powerful in predicting the Cboe volatility index compared to COVID-19-infected cases in the world and China(MAPE(2.1013%);R2(91.78%)and RMSE(0.6363 percentage points)).The proposed approaches have also shown good convergence characteristics and accurate fits of the data.

A Novel Approach to Reduce Handover Latency in Proxy Mobile IPv6 Based on Multi-Homing

Proxy Mobile IPv6 (PMIPv6) is a network based mobility management protocol. It is proposed by the Internet Engineering Task Force. In PMIPv6 the Mobile Node (MN) need not participate in signalling of mobility. PMIPv6 is a layer 3 protocol. In this paper the issue of layer 3 mobility is resolved by the Enhanced Open Flow Technique (EOFT). Generally, the open flow protocol makes functions on network devices, routers, switches. Open flow controller act as server for network devices to make communication between them. In the proposed EOFT-PMIPv6, the control signalling and mobility is managed by EOFT controller. In PMIPv6, the Mobility Access gateway (MAG) has the responsibility of the control signalling. But in the EOFT-PMIPv6, the responsibility of MAG is done by the EOFT-Controller. In the proposed technique, the mobility management function is isolated from PMIPv6 mechanisms. These isolated mechanisms are combined in the EOFT-Con- troller. This EOFT-Controller satisfies the responsibility of the mechanisms which are separated from PMIPv6. The eminent mobile environment must provide the efficient multi-homing protocols. The proposed technique overcomes the problem of multihoming in PMIPv6. The EOFT-Controller takeover the responsibility of Layer 3 functions. Also, the proposed technique combines with Modified Mobility Access Gateway (M_MAG) and it handles the handover session dynamically. This paper provides the extended architecture of EOFT-PMIPv6 and provide unbeaten handover scheme for multi-homing. The result is provided by systematic analysis based on comparison with PMIPv6 and EOFT-PMIPv6 is obtained.

An Approach for Damage Identification and Optimal Sensor Placement in Structural Health Monitoring by Genetic Algorithm Technique

Civil engineering structures are constructed for strength, serviceability and durability. The structures thus constructed involve huge investment and labour work. In order to protect the structure from various damages, periodic monitoring of structures is necessary. Hence Structural Health Monitoring (SHM) plays a vital role in diagnosing the state of the structure at every moment during its life period. For this purpose, sensors are deployed in the structures for its efficient health monitoring. Sensors cannot be deployed at random locations of the structure. They have to be located at those points which reflect the damage. In this study, a 3-storey and a 4-storey building are taken and Modal Strain Energy (MSE) is used for finding the initial locations of sensors. The number of sensors obtained is then optimized using Genetic Algorithm (GA) technique. Finally damages are induced in certain locations of the structure and a damage detection technique called as “Flexibility Matrix Based Technique (FMBT)” is introduced for damage localization in the structure.

Investigation of a practical load model for a natural gas explosion in an unconfined space

Natural gas is extensively used as a clean energy source in cities and industries;consequently,there are associ-ated risks of accidental explosions.To reduce the hazards associated with natural gas explosions,it is important to study the inherent laws of natural gas blast loads in unconfined spaces and establish load models.Using ex-periments on natural gas explosions in unconfined spaces,this study demonstrates the influence of natural gas concentrations,propagation distances,and gas volumes upon explosion loads.A new load model was proposed for the overpressure-time history curves of natural-gas explosions in an unconfined space.A comparison with the empirical model indicated that the predictive effect was superior to that of previous models,such as the TNT equivalent model and the TNO multi-energy model.

Investigation of a semi-empirical load model of natural gas explosion in vented spaces

Due to the influence of many factors,the overpressure-time history load model of vented gas explosions is difficult to describe and is not conducive to further structural design.Based on vented gas explosion test data,this paper obtains three typical overpressure-time history curves and puts forward a new semi-empirical model-double hump model that considers gas concentration and venting pressure,and gives a formula for peak pressure and overpressure-time history model.The scientificity of the model is then verified by the total impulse in the load.The model is able directly reflect the load characteristics,provide reference for calculating key parameters of a vented gas explosion and provide information on the structural response under the load.The model thereby has the potential to help reduce the impact of gas explosion disasters.

A Shoreline Change Analysis Along the Coast Between Kanyakumari and Tuticorin, India, Using Digital Shoreline Analysis System

The shoreline is one of the rapidly changing landforms in coastal areas.They are the key element in coastal GIS and provide the most information on coastal land form dynamics.Therefore,accurate detection and frequent monitoring of shorelines is very essential to understand the coastal processes and dynamics of various coastal features.The present study is to investigate the shoreline changes along the coast between Kanyakumari and Tuticorin of south India(where hydrodynamic and morphologic changes occur continuously after the December 2004 tsunami)by using Digital Shoreline Analysis System(DSAS),an extension of ArcGIS.Multidate IRS and Landsat Satellite data(1999,2001,2003,2005,2007,and 2009)are used to extract the shorelines.The data is processed by using the ERDAS IMAGINE 9.1 software and analyzed by ArcGIS 9.2 workstation.The rates of shoreline changes are estimated by three statistical methods,namely,End Point Rate(EPR),Linear Regression Rate(LRR),and Least Me-dian of Squares(LMS)by using DSAS.The study reveals that most of the study area has undergoing erosion.Both natural and an-thropogenic processes along the coast modify the shoreline configuration and control the erosion and accretion of the coastal zones.The coastal zones along the estuary have experienced accretion due to the littoral processes.The zones with headlands have more eroded than other zones along the study area.The study also shows that the coastal zones where sand is mined have relatively more rate of erosion than that of the other zones.Improper and unsustainable sand mining may also lead to severe erosion problem along this area.The shoreline change rates are altered by various geological processes along the coast.Thus,the present study implies that proper beach filling and nourishment projects should be made in the study area to save from hazards.It also indicates the advantage and suitability of DSAS to assess the shoreline changes compared with the traditional manual shoreline change analysis and prom-ising its applications for coastal zone management in other regions.