A Stipulation Based Sources Insertion Multilevel Inverter (SBSIMLI) for Waning the Component Count and Separate DC Sources

Edwin Jose S,Titus S 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.4

The paper proposes a well structured, component count waned single phase multilevel inverter (MLI) topology, which drives three different modules viz. Stipulation Based Sources Insertion (SBSI) module, Level Count Increasing (LCI) module and Inter-Linking H-Bridge (ILHB) module. The SBSI module confronts the number of basic sources needed in series/parallel to achieve required magnitude for any particular level. The LCI possesses an offsetting dc source and opuses to increase the number of levels and the ILHB module links the SBSI and LCI modules. A developed Hybrid Pulse Width Modulation (HPWM) strategy has PWM pulses for the switches of LCI module while the switches of the remaining two modules function at fundamental switching frequency. A fifteen level version of the proposed stipulation based sources insertion MLI (SBSIMLI) topology is simulated in MATLAB R2010a and a prototype of the similar specifications is constructed to validate the performance by experimental results. The comparison between the developed SBSIMLI topology and the competent topologies shows many interesting facts.

A Level Dependent Source Concoction Multilevel Inverter Topology with a Reduced Number of Power Switches

Edwin Jose, S.,Titus, S. The Korean Institute of Power Electronics 2016 JOURNAL OF POWER ELECTRONICS Vol.16 No.4

Multilevel inverters (MLIs) have been preferred over conventional two-level inverters due to their inherent properties such as reduced harmonic distortion, lower electromagnetic interference, minimal common mode voltage, ability to synthesize medium/high voltage from low voltage sources, etc. On the other hand, they suffer from an increased number of switching devices, complex gate pulse generation, etc. This paper develops an ingenious symmetrical MLI topology, which consumes lesser component count. The proposed level dependent sources concoction multilevel inverter (LDSCMLI) is basically a multilevel dc link MLI (MLDCMLI), which first synthesizes a stepped dc link voltage using a sources concoction module and then realizes the ac waveform through a conventional H-bridge. Seven level and eleven level versions of the proposed topology are simulated in MATLAB r2010b and prototypes are constructed to validate the performance. The proposed topology requires lesser components compared to recent component reduced MLI topologies and the classical topologies. In addition, it requires fewer carrier signals and gate driver circuits.

A Stipulation Based Sources Insertion Multilevel Inverter (SBSIMLI) for Waning the Component Count and Separate DC Sources

Edwin, Jose S,Titus, S The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.8 No.1

The paper proposes a well structured, component count waned single phase multilevel inverter (MLI) topology, which drives three different modules viz. Stipulation Based Sources Insertion (SBSI) module, Level Count Increasing (LCI) module and Inter-Linking H-Bridge (ILHB) module. The SBSI module confronts the number of basic sources needed in series/parallel to achieve required magnitude for any particular level. The LCI possesses an offsetting dc source and opuses to increase the number of levels and the ILHB module links the SBSI and LCI modules. A developed Hybrid Pulse Width Modulation (HPWM) strategy has PWM pulses for the switches of LCI module while the switches of the remaining two modules function at fundamental switching frequency. A fifteen level version of the proposed stipulation based sources insertion MLI (SBSIMLI) topology is simulated in MATLAB R2010a and a prototype of the similar specifications is constructed to validate the performance by experimental results. The comparison between the developed SBSIMLI topology and the competent topologies shows many interesting facts.

A Level Dependent Source Concoction Multilevel Inverter Topology with a Reduced Number of Power Switches

S. Edwin Jose,S. Titus 전력전자학회 2016 JOURNAL OF POWER ELECTRONICS Vol.16 No.4

Multilevel inverters (MLIs) have been preferred over conventional two-level inverters due to their inherent properties such as reduced harmonic distortion, lower electromagnetic interference, minimal common mode voltage, ability to synthesize medium/high voltage from low voltage sources, etc. On the other hand, they suffer from an increased number of switching devices, complex gate pulse generation, etc. This paper develops an ingenious symmetrical MLI topology, which consumes lesser component count. The proposed level dependent sources concoction multilevel inverter (LDSCMLI) is basically a multilevel dc link MLI (MLDCMLI), which first synthesizes a stepped dc link voltage using a sources concoction module and then realizes the ac waveform through a conventional H-bridge. Seven level and eleven level versions of the proposed topology are simulated in MATLAB r2010b and prototypes are constructed to validate the performance. The proposed topology requires lesser components compared to recent component reduced MLI topologies and the classical topologies. In addition, it requires fewer carrier signals and gate driver circuits.

Bivariate odd-log-logistic-Weibull regression model for oral health-related quality of life

Cruz, Jose N. da,Ortega, Edwin M.M.,Cordeiro, Gauss M.,Suzuki, Adriano K.,Mialhe, Fabio L. The Korean Statistical Society 2017 Communications for statistical applications and me Vol.24 No.3

We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.

An Integrated EMVO and ARBFN Algorithms for Output Power Forecasting and Fault Prediction in Solar PV Systems

Manoj C. R.,Jose S. Edwin 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.5

Predicting the output power and detecting the faults on the solar photovoltaic (PV) systems are the challenging tasks in the modern decades. The conventional works are highly focused on developing an optimization and classification methodologies for accomplishing PV output power forecasting and fault prediction separately. But, this paper focused on solving a multi-objective research problem by implementing an innovative optimization and classification methodologies. For obtaining the maximum power yield from the solar PV panels, the maximum peak point tracking controlling technique is used in this system. In the first stage of work, the PV output power prediction is performed by deploying an endowed multi-verse optimization (EMVO) methodology. This technique intends to improve the convergence rate of optimization by estimating the best fitness value. For computing the best fitness value, the nonlinear inertial weight has been estimated with respect to the distance near the optimal universe. Also, the selection operation is performed to obtain the survival of the fittest value based on the crossover probability and random dimension value. Based on this, the power prediction can be performed with the operations of crossover, mutation and selection. In the second stage of work, the fault detection is mainly concentrated to ensure the normal operations on the PV system. For this purpose, an augmented radial basis functional network (ARBFN) technique is implemented for exact fault detection. In the proposed work, the EMVO and ARBFN methodologies are mainly used for accomplishing the objectives of PV output power forecasting and fault prediction at earlier stage. Here, the set of wavelet patterns have been extracted and used for training the classifier, which improves the overall accuracy rate of fault classification. Moreover, the experimental results evaluate the performance of both power prediction and fault detection techniques by using various measures. By using the proposed EMVO–ARBFN mechanisms, the absolute error value is reduced up to 0.2%, relative error is reduced to 3%, accuracy of prediction is increased to 98%, and fault mis-classification rate is minimized to 2.5%. Also, the obtained results have been compared with the existing approaches for proving the superiority of the proposed system, which includes the pre-turn method, back propagated neural network, artificial neural network, support vector machine, support vector regression, and other integrated machine learning models.