Voltage lifting techniques are employed invariably in high step-up applications to provide an enhanced voltage transfer and power gain, as it alleviates the problems encountered in operating the converter at an extreme duty ratio. Ripple content present in output of power converter would tend to affect the load performance. Hence soft-switched single ended primary inductor converter (SSSEPIC) is proposed between solar system and load to curtail the ripple content. This work deals with the simulation of SEPIC triple-lift converter system (SEPIC-TLCS) in closed loop mode of operation. The voltage ripple in output is minimized by connecting a T-filter. The prime objective of this work is to obtain a good regulated dc output voltage. The simulation studies are performed using Matlab Simulink models developed for proportional integral controlled closed loop SEPIC triple-lift converter system (PI-CLSTLCS) and fuzzy controlled closed loop SEPIC triple-lift converter system (FC-CLSTLCS). Time domain parameters are compared and comparative results illustrate the superior performance of FC-CLSTLCS. Therefore it can be used as a substitute for the existing dc-dc converters.

In this paper, we study certain new difference sequence spaces by using Hilbert sequence space defined by Orlicz function. We characterize some topological properties and inclusion relations involving these sequence spaces.

An attempt is made to analyse the effects of skin friction on unsteady flow past a moving vertical plate in a rotating fluid with variable temperature and mass diffusion. An analytical solution is obtained by considering a complex velocity with the axial and transverse components. The effects of skin friction for the parameters like Schmidt number, radiation parameter, thermal Grashof number Prandtl number, rotation parameter and mass Grashof number on the plate are observed and analysed.

The most fundamental step in image processing is image segmentation and it results in revealing enormous information embedded in most widely used RGB color space image. Excellent result is obtained for bi-level thresholding and the exhaustive search for optimal threshold values, to analyze complex images in multilevel thresholding (MLT), is reduced by promising objective functions such as Otsu and minimum cross entropy MCE aided with teaching-learning based optimization metaheuristic algorithm (TLBO). In TLBO, a teacher shares cognizance to a student. The use of only common control parameters and less-specific control parameters in TLBO achieves exploration and exploitation. The efficiency of TLBO is compared with cuckoo search algorithm (CS) at 4,5,6 and 7 threshold levels. Experimental results reveal that optimal output of TLBO is more successful in precise image segmentation and aids in various real time applications.

Voltage lift cascaded DC/DC converters are generally used to feed low power DC drives and batteries. This paper deals with the modelling, the simulation and the comparison of voltage lifted Single Ended Primary Inductor Converter (SEPIC) cascaded soft switched converter systems. The objective of this work is to improve the voltage gain and the efficiency of the voltage lifted SEPIC converter. Auxiliary switch with capacitor clamping is added in order to obtain the soft switching. SEPIC in self-lift and re-lift modes are simulated and the corresponding results are presented. The performance of the converter is studied in terms of output power and ripple voltage. Design and simulation results are presented in order to identify a cascaded system with high power output. The comparative study is presented in order to demonstrate the reduction in the ripple in the output voltage. The advantages of the proposed converter are high voltage gain, reduced switching loss and low electromagnetic interference (EMI). The open loop systems with fluctuating input voltages are simulated. Closed loop systems with proportional integral controller and Fuzzy Logic Controller (FLC) are simulated and their results are compared. Comparing the results, it can be observed that the time response has been improved in terms of settling time and steady state error.

ﺔﺸﻗﺎﻨﻣ ﺔﺣﻮﻠﻟا ﻲﻓ ﺖﻗﻮﻟا . Theoretical study of thermal radiation effects on unsteady flow past a moving vertical plate in a rotating fluid with variable temperature and uniform mass diffusion is considered. An exact solution is obtained for the axial and transverse components of the velocity by defining a complex velocity. The effects of velocity, temperature and concentration for different parameters like radiation parameter, rotation parameter, Schmidt number, thermal Grashof number, mass Grashof number, Prandtl number and time on the plate are discussed.

Theoretical study of thermal radiation effects on unsteady free convection and variable mass diffusion over a moving vertical plate in a rotating fluid is considered. An exact solution is obtained for the axial and transverse components of the velocity by defining a complex velocity. The effects of velocity, temperature and concentration for different parameters like radiation parameter, rotation parameter, Schmidt number, thermal Grashof number, mass Grashof number, Prandtl number and time on the plate are discussed.

This paper is intended to generate unbiased state estimates of a three-phase induction motor using derivative-free state estimation algorithms. The use of intrusive sensors located within the air-gap of the machine has typically been plagued by complexities and lack of robustness. Moreover, any eventual damage in the sensor results in the substitution of the whole motor. On the other hand, there have been major efforts to reduce the cost of high performance systems, besides increasing the versatility of the motor that all necessitate the use of state observers, thereby eliminating the sensors and their interfaces. In this work, a comparative analysis of the three derivative-free non-linear filtering schemes to estimate the states of a three-phase induction motor on the simulated model is presented. The efficacy of ensemble Kalman filter (EnKF) against the traditional sampling importance re-sampling particle filter (SIR-PF) and unscented Kalman filter (UKF) is illustrated. Comparative Monte Carlo simulation results are investigated comprehensively with respect to three different scenarios, namely step changes in load torque, speed reversal, and low speed operation. Computer simulations have been carried out in the presence of additive state and measurement uncertainties and from the extensive simulation studies, it is being inferred that the SIR-PF fails to generate accurate state estimates in the presence of step changes in the load torque as it does not take into account the most current observation in the sampling stage, whereas EnKF and UKF work well. Moreover, when compared on the basis of the sum of squares of the estimation errors (SSEE), which is very often used as the performance index, the performance of the unconstrained estimation algorithm using the EnKF is found to be significantly better than those obtained using UKF and SIR-PF formulations for all the scenarios taken for the simulation study. The results throw light on alleviating the intrinsic intricacies encountered in SIR-PF in parlance with the observer theory.Key Words: Ensemble Kalman filter (EnKF)sampling importance re-sampling particle filter (SIR-PF)Bayesian state estimationthree phase induction motor (IM)unscented Kalman filter (UKF) Additional informationNotes on contributorsJ. RavikumarJ. Ravikumar received his BE and ME degrees in Electrical Engineering from Annamalai University, Annamalainagar, India, in 1993 and 1995, respectively. He is currently an Assistant Professor with the Department of Electrical Engineering, Annamalai University. His principal research interests are Bayesian state estimation, electrical machines and speed-sensorless AC drives.S. SubramanianS. Subramanian is currently with the Department of Electrical Engineering, Annamalai University, Annamalainagar, India, as a Senior Professor. He has authored 140 research articles in various international journals, national journals, international conferences and national conferences. His current research interests include power system operation and control, design analysis of electrical machines, power system state estimation, and power system voltage stability studies. He is a Senior Member IEEE and a Fellow of Institution of Engineers.J. PrakashJ. Prakash received his BE degree in Electronics and Instrumentation Engineering from Annamalai University, Annamalainagar, India, in 1993, ME degree with specialisation in Control Systems from Bharathiar University, Coimbatore, India, in 1995, and PhD in Process Control from IIT, Chennai, India, in 2001. Since 2003, he has been an Associate Professor in the Instrumentation Department of Madras Institute of Technology, Chennai, India. He has presented, authored and co-authored more than 50 technical papers in his research areas of process control, non-linear state observers, fault detection, and diagnosis and model predictive control in various refereed international/national journals and conferences.

Particle filters are an alternative to approximate the Kalman filter for nonlinear problems.This paper intends to assess the potential of Particle Filter (PF) and its variants in the context of the state estimation problem of a three phase induction motor.The conventional Particle Filter (SIR-PF), and particle filters that employ importance sampling through proposal distributions such as Particle Filter with Extended Kalman Filter (PF-EKF) and Particle Filter with Unscented Kalman Filter (PF-UKF), which are proposed in the literature within the particle filtering framework that takes into account of the latest observational information to reduce the risk of weight degeneracy is described and the error behaviour is analyzed through Monte Carlo simulations with regard to three scenarios Viz., low speed operation, step changes in load torque and reversal of speed.Simulation results demonstrate the superior tracking performance of PF-EKF at the expense of higher computational effort over the other approaches and can be determined to be a good substitute for the UKF in terms of accuracy of the state vector estimation.