In this paper water cycle algorithm based fractional order PI controller (FOPI) is proposed for virtual flux oriented control of three phase grid connected PWM rectifier. FOPI controller makes the PWM rectifier control more robust due to the fractional behavior. Fractional order controllers have additional degree of freedom and so wider range of parameters is available to provide better control and robustness in the plant. The optimization and design of FOPI controller is done using water cycle algorithm (WCA). WCA is an optimization method inspired by monitoring the water cycle operation and flow of water bodies like streams and rivers in the direction of sea. The performance of FOPI controller is compared with classical integer order PI controller. The parameters of PI and FOPI controllers are optimized and designed using WCA technique leading to WCA-PI and WCA-FOPI controllers. The system is tested using MATLAB/Simulink. The simulati on results verify the better performance of WCA-FOPI in terms of settling time, rise time, peak oversh oot and Total Harmonic Distortion (THD) of grid current. A robustness measurement with line filter parametric variations and non ideal supply voltage (unbalance and distorted supply voltage) is carried out. The WCA-FOPI demonstrates more robustness as compared to WCA-PI. Simulation findings validate the WCA-FOPI controller outcomes as compared to WCA-PI in terms of control effect and robustness.
The steady state analysis of self excited induction generator (SEIG) is vital for proper implementation of induction machine operation as a generator in a stand alone mode through appropriate modeling. This paper presents a user friendly software based solution for complete evaluation of steady-state behavior of SEIG under different operating conditions.The mathematical modeling of the machine is carried out and then simulated in MATLAB's Graphical User Interface (GUI) environment and active windows are created with these models.The simulation results obtained through the presented methodology are validated through relevant experimental verification.Index Terms-Analysis, Effect of Capacitance ,Graphical user interface (GUI), MATLAB simulation, Self excited induction generator (SEIG),
Steady state analysis of single-phase self excited induction generator is almost always carried out using the concepts of symmetrical components and the rotating field theories. The machine is modeled through its positive and negative sequence circuits with appropriate parameters pertaining to forward and backward fields. The final expression obtained through these analyses is a complex nonlinear equation with magnetizing reactance and frequency as two unknown quantities. Once the equation is solved and the values of magnetizing reactance and frequency precisely evaluated, the analysis of the machine performance becomes straight forward. This paper presents the use of "fsolve" optimization tool of Matlab in solving this complex equation yielding magnetizing reactance and frequency which, finally helps in the complete steady state analysis of the single-phase self excited induction generator. The method is found to be elegant and user-friendly.
Data used in the present study are from the National Family Health Survey (NFHS-I) 1992-93 (International Institute for Population Sciences 1995), India. Our study has developed Cox model analyses to see the effect of breastfeeding as a time-varying and time-dependent factor on birth spacing. While it is acknowledged that breastfeeding has a protective effect on birth spacing, such analysis of breastfeeding allows for a more nuanced understanding of that effect. Multivariate analysis revealed that breastfeeding, ever experience of fetal loss, education of women, employment status of women, education of husband, media exposure, survival status of index child and place of residence played an important part in extending birth space in at least one of the birth-spacing intervals (first to fifth). However, the variables varied from the first birth spacing to the fifth birth spacing. Breastfeeding is the only covariate found to be a significant protective factor associated with each birth spacing. Furthermore, this study validates the developed models with their prediction utilities for birth spacing.
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