The presence of harmonics in solar Photo Voltaic (PV) energy conversion system results in deterioration of power quality. To address such issue, this paper aims to investigate the elimination of harmonics in a solar fed cascaded fifteen level inverter with aid of Proportional Integral (PI), Artificial Neural Network (ANN) and Fuzzy Logic (FL) based controllers. Unlike other techniques, the proposed FLC based approach helps in obtaining reduced harmonic distortions that intend to an enhancement in power quality. In addition to the power quality improvement, this paper also proposed to provide output voltage regulation in terms of maintaining voltage and frequency at the inverter output end in compatible with the grid connection requirements. The simulations are performed in the MATLAB / Simulink environment for solar fed cascaded 15 level inverter incorporating PI, ANN and FL based controllers. To exhibit the proposed technique, a 3 kWp photovoltaic plant coupled to multilevel inverter is designed and hardware is demonstrated. All the three techniques are experimentally investigated with the measurement of power quality metrics along with establishing output voltage regulation.

In recent years, the suspension system in modern vehicles has played a key role both as far as driving safety and comfort is concerned. To satisfy these vehicle performance specifications,active suspension is currently studied and implemented in practice in recent decades.In contrast to passive suspensions, by introducing force into system, active suspension can alter the suspension dynamic in real-time. A design of a controller is needed for real-time tuning of the control force in an active suspension system (ASS) to fulfill the challenging control objectives of suspension system comprising road handling, ride convenience, and travel suspension. This research proposed a novel ant colony optimization (ACO) algorithm for solving multi-objective weight optimization problem of the linear quadratic regulator (LQR) for automobiles ASS. The optimization problem of ASS is to design a state-feedback controller (SFC) as a result ACO is used to find optimal LQR weights. Here bothQ and R weight matrix of LQR is tuned. On a quarter-car ASS (QCASS) system, the effectiveness of ACO-tuned LQR is analytically checked with hardware in loop (HIL) analysis for an irregular road surface. Here, forexperiment, ISO road D rough runway, bumpy path, and pulse-type road profile are taken into account. Experimental findings illustrate that the proposed procedure can substantially reduce the acceleration of the Car body due to irregular road profiles compared to classical tuned LQR and model predictive control (MPC). The proposed controller shows the profound impact on the efficiency of the control schemes for three different road profiles.

This paper presents the design and implementation of Modular Multilevel Inverter (MMI) to control the Induction Motor (IM) drive using intelligent techniques towards marine water pumping applications. The proposed inverter is of eleven levels and has the ability to control the speed of an IM drive which is fed from solar photovoltaics. It is estimated that the energy consumed by pumping schemes in an onboard ship is nearly 50% of the total energy. Considering this fact, this paper investigates and validates the proposed control design with reduced complexity intended for marine water pumping system employing an induction motor (IM) drive and MMI. The analysis of inverter is carried out with Proportional-Integral (PI) and Fuzzy Logic (FL) based controllers for improving the performance. A comparative analysis has been made with respect to better robustness in terms of peak overshoot, settling time of the controller and Total Harmonic Distortion (THD) of the inverter. Simulations are undertaken in MATLAB/Simulink and the detailed experimental implementation is conducted with Field Programmable Gate Array (FPGA). The results thus obtained are utilized to analyze the controller performance, improved inverter output voltage, reliable induction motor speed control and power quality improvement by reduction of harmonics. The novelty of the proposed control scheme is the design and integration of MMI, IM drive and intelligent controller exclusively for marine water pumping applications.

The study lowers the environmental risk by combining biodegradable adsorbents with stronger adsorption. This work uses two distinct kinds of adsorbents, namely Polyaniline (PANI) coated Kappa Cotton (KPC) and activated clay-biopolymer, Bentonite (aB) composite and Chitosan (CTN), to recover the aged transformer oil (aTO). Using the Box-Behnken (BB) design paired response surface method (RSM) approach, an experimental sequence was created to determine the optimal ratio of the adsorbent materials. The aTO was supplemented with the homogenized aB-CTN material (A*) and PANI-coated-KPC (B*) materials. After optimization, it was found that the optimal values for the input variables for the dielectric breakdown voltage and dielectric dissipation factor were A* = 1.76 g, B* = 1.28 g, temperature = 78.9 °C, while stirring duration = 3 h was kept constant. After treatment under ideal conditions, it was found that aTO1 had dielectric characteristics of 46.6 kV and 0.0020 dissipation factor, which are equivalent to those of laboratory studies conducted in triplicate with a 2.5 percent error. They demonstrate that aTO exhibits an outstanding dielectric response when the optimal proportion of the process variables (A* and B*) is used. The removal of impurities from aTO has considerably enhanced its dielectric properties, as seen by the CIE chromaticity coordinates, XRD analysis, UV responses, and FTIR analyses. The material’s ability to sorb dyes, polar impurities, and heavy metal ions is significantly increased by the expanded active sites of A* and B*.

In this present work, effort was taken to develop a response surface model based on response surface methodology (RSM) paired with Box–Behnken design (BBD). Investigations were carried out to optimize the transesterification of Pongamia Pinnata oil (PPO) under various process conditions such as time (60–180 min), temperature (60 °C–100 °C), and catalyst (1%–3%). The production of PPO methyl ester (PPOME) by the esterification process is carried out using the PPO and methanol (CH3OH) in a 1:6 molar ratio that is fixed as a constant. Here, the input variables are the process variables (independent) and the output variables are the response variables (dependent). The response variables are the breakdown voltage (BDV), kinematic viscosity (KV), and fire point (FRP). The effect of the process variables on the response variables is modeled using RSM paired BBD. The experimental sequence was designed to find the optimum composition of input parameters and output parameters. The associative effects of the input and output variables were designed as a 2-D contour plot and 3-D response surface plots, and the interactive effects were studied using the plots. After optimization, the optimum conditions of the input variables over the BDV, KV, and FRP were found to be the time of 142.07 min, the temperature of 81.52 °C, and the catalyst of 2.41%. The dielectric properties of PPOME were found to be 61.54 kV, 20.50 cSt, and 281.43 °C, which are in the vicinity of the laboratory experimental results. Those indicate that the treatment of PPO with the optimum quantity of the process variables gives an excellent dielectric response.

This research investigates a tropical indigenous nonedible ester such as Pongamia oil (PO). PO and PO methyl ester (POME) were taken as test samples to develop a nonparametric model for investigations. This work implements the empirical cumulative distribution function (eCDF) to develop a PO and POME lifetime model. The lifetime model of the PO and POME acts as a decisive factor in determining the early failure regions corresponding to the bathtub model. On the other hand, the Bayesian theorem calculates the Bayesian inference. This enables one to foresee the variable as a posterior distribution to conclude their correlation in the parameter space. The developed lifetime model of PO and POME supports experimental results over hypothesis and assists one to predict the risk probability. The model predicted early failures of the PO at less than 40 kV and POME at less than 54 kV and life of POME from 41 to 54 kV and POME at 55–65 kV. The useful life of PO and POME will experience a failure rate of 45% and 25%, respectively. Furthermore, such detections aid power engineers to treat insulating fluids to overcome early aging effects and deterioration of oil–paper insulation.