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Introduction. When the working point of the indirect vector control is constant, the conventional speed and current controllers operate effectively. The operating point, however, is always shifting. In a closed-system situation, the inverter measured reference voltages show higher harmonics. As a result, the provided pulse is uneven and contains more harmonics, which enables the inverter to create an output voltage that is higher. Aim. A space vector modulation (SVM) technique is presented in this paper for type-2 neuro fuzzy systems. The inverter’s performance is compared to that of a neuro fuzzy type-1 system, a neuro fuzzy type-2 system, and classical SVM using MATLAB simulation and experimental validation. Methodology. It trains the input-output data pattern using a hybrid-learning algorithm that combines back-propagation and least squares techniques. Input and output data for the proposed technique include information on the rotation angle and change of rotation angle as input and output of produced duty ratios. A neuro fuzzy-controlled induction motor drive’s dynamic and steady-state performance is compared to that of the conventional SVM when using neuro fuzzy type-2 SVM the induction motor, performance metrics for current, torque, and speed are compared to those of neuro fuzzy type-1 and conventional SVM. Practical value. The performance of an induction motor created by simulation results are examined using the experimental validation of a dSPACE DS-1104. For various switching frequencies, the total harmonic distortion of line-line voltage using neuro fuzzy type-2, neuro fuzzy type-1, and conventional based SVMs are provided. The 3 hp induction motor in the lab is taken into consideration in the experimental validations.

This paper presents a photovoltaic system with maximum power point tracking facility. Maximum power point trackers are so important in photovoltaic systems to increase their efficiency. The system consists of a photovoltaic solar module connected to a DC–DC buck–boost converter and load. The adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) controller is used to track the maximum power. DC–DC boost converter and space vector modulation-based inverter are used to provide the required supply to the load. The proposed ANFIS-based MPPT improves the system efficiency even at abnormal weather conditions. Here a lot of reduction in torque and current ripple contents is obtained with the help of ANFIS-based MPPT for an asynchronous motor drive. Also, the better performance of an asynchronous motor drive is analyzed with the comparison of conventional and proposed MPPT controller using MATLAB simulation along with experimental implementation. The experimental implementation of MPPT with hardware setup is done using dSPACE real-time controller. Data acquisition and codes of the successfully simulated model can be linked and loaded directly to the dSPACE DS-1104 controller for real-time hardware operation. The simulation and the practical results represent that the proposed system tracked the maximum power accurately and successfully under different working conditions. Practical validations are also carried out and are represented.

Carbide-free bainitic steels are known for their very high strength because of their fine nanoscale hard bainitic ferrite and inter-layer ductile retained austenite. The mechanical properties of these steels are influenced by the size, fraction, and morphology of constituent bainite and retained austenite phases. Prior austenite microstructure plays an important role in determining the morphology and volume fraction of bainite and retained austenite resulting from the austempering treatment. In the present study, mechanical properties of two high-carbon, high-silicon, carbide-free bainitic steels with and without niobium addition austenitized at three different temperatures (900 °C, 970 °C, and 1050 °C) and austempered at 300 °C for 12 h are reported. Both the steels show a decrease in total elongation and Charpy V-notch impact toughness with increasing austenitization temperature. Niobium addition significantly refines the prior austenitic grain size at any given austenitization temperature, which improves total elongation and Charpy V-notch impact toughness.

Background Several small molecule corrector and potentiator drugs have recently been licensed for Cystic Fibrosis (CF) therapy. However, other aspects of the disease, especially inflammation, are less effectively treated by these drugs. We hypothesized that small molecule drugs could function either alone or as an adjuvant to licensed therapies to treat these aspects of the disease, perhaps emulating the effects of gene therapy in CF cells. The cardiac glycoside digitoxin, which has been shown to inhibit TNFα/NFκB signaling in CF lung epithelial cells, may serve as such a therapy. Methods IB3–1 CF lung epithelial cells were treated with different Vertex (VX) drugs, digitoxin, and various drug mixtures, and ELISA assays were used to assess suppression of baseline and TNFα-activated secretion of cytokines and chemokines. Transcriptional responses to these drugs were assessed by RNA-seq and compared with gene expression in AAV-[ wildtype ]CFTR-treated IB3–1 (S9) cells. We also compared in vitro gene expression signatures with in vivo data from biopsied nasal epithelial cells from digitoxin-treated CF patients. Results CF cells exposed to digitoxin exhibited significant suppression of both TNFα/NFκB signaling and downstream secretion of IL-8, IL-6 and GM-CSF, with or without co-treatment with VX drugs. No evidence of drug-drug interference was observed. RNA-seq analysis showed that gene therapy-treated CF lung cells induced changes in 3134 genes. Among these, 32.6% were altered by digitoxin treatment in the same direction. Shared functional gene ontology themes for genes suppressed by both digitoxin and gene therapy included inflammation (84 gene signature), and cell-cell interactions and fibrosis (49 gene signature), while genes elevated by both were enriched for epithelial differentiation (82 gene signature). A new analysis of mRNA data from digitoxin-treated CF patients showed consistent trends in expression for genes in these signatures. Conclusions Adjuvant gene therapy-emulating activities of digitoxin may contribute to enhancing the efficacy of currently licensed correctors and potentiators in CF patients.

Solar photovoltaic (PV) energy stands as a predominant source of renewable power. The efficiency of energy conversion from sunlight via photovoltaic panels is subject to fluctuation due to varying solar intensity and radiation levels. To optimize the power output, the Maximum Power Point Tracking (MPPT) technique is pivotal. Among the various methods available, high- performance soft computing techniques serve as robust MPPT strategies. This paper introduces a Fuzzy Logic Controller (FLC)-based MPPT system for grid-connected PV systems operating under both steady and variable climatic conditions. The FLC-based MPPT system adeptly adjusts the PV system’s voltage, current, and power settings to harness the maximum feasible power output from the photovoltaic panels. Simulation outcomes demonstrate that the FLC- based MPPT system outperforms the conventional Perturb and Observe (P&O) MPPT method. The employment of a fuzzy logic-controlled grid connection for PV systems heralds significant enhancements in the efficiency, stability, and reliability of integrating renewable energy into the electrical grid. Leveraging fuzzy logic algorithms, this technique allows for dynamic power management, precise voltage regulation, and enhanced frequency stability, effectively mitigating the issues inherent to intermittent solar power. A notable strength of this approach is its inherent flexibility, adapting in real-time to fluctuating environmental and grid conditions, thereby optimizing system performance across diverse scenarios. Furthermore, the implementation of a fuzzy logic- controlled grid connection ensures smooth integration of PV systems into the grid, reducing risks associated with grid disturbances, voltage fluctuations, and frequency anomalies. This strategy not only bolsters the reliability of renewable energy sources but also enhances grid resilience against variable demand and generation dynamics. In summary, the integration of fuzzy logic-controlled connections presents a forward-thinking solution that significantly advances PV system integration into the grid, yielding marked improvements in efficiency, reliability, and overall grid stability. Fuzzy logic-based MPPT offers a robust and adaptable approach to tracking the maximum power point in grid-connected PV systems, overcoming some of the limitations of traditional methods like P&O.

Carbide free nano-structured bainitic steels typically have strength more than 2.0 GPa and impact toughness of 7 J or less. Most of this class of steels have sluggish kinetics and takes 16-72 h for complete bainitic transformation. The present work discusses key perspectives in developing carbide free nano-structured bainitic steel having strength more than 2.0 GPa and toughness more than 15 J. Further, ballistic evaluation of newly developed carbide free nano-structured bainitic steels having strength more than 2.0 GPa and high toughness of 20 J was carried out to understand the adaptability of these steels in combat vehicle applications. A comparison is made between newly developed high strength and tough carbide free nano-structured bainitic steels with typical martensite based ARMOX 500 class of armour steels. The developed nano-structured bainite showed ballistic performance much superior to ARMOX 500 steel. Monolithic plates of bainite provide complete protection against 7.62 AP projectiles at an areal density of 120 kgm-2. The ballistic efficiency of monolithic plates was further enhanced by using perforated geometrical configurations.

In portable cloud organizations (MCNs), a versatile client is associated with a cloud worker through an organization entryway, which is answerable for giving the necessary nature of-administration (QoS) to the clients. On the off chance that a client expands its administration interest, the associating passage may neglect to give the mentioned QoS because of the over-burden interest, while different entryways remain underloaded. Because of the expansion in burden in one Gateway, the sharing of burden among all the passages is one of the imminent answers for giving QoS-ensured administrations to the portable clients. Moreover, if a client makes trouble, the circumstance turns out to be all the more testing. In this paper, we address the issue of QoS-ensured made sure about help provisioning in MCNs. We plan a utility boost issue for quality-guaranteed made sure about burden sharing (QuaLShare) in MCN, and decide its ideal arrangement utilizing sell off hypothesis. In QuaLShare, the over-burden passage identifies the getting out of hand Gateways, and, at that point, keeps them from partaking in the closeout cycle. Hypothetically, we portray both the issue and the arrangement approaches in a MCN climate. At last, we explore the presence of Nash Equilibrium of the proposed plot. We expand the answer for the instance of different clients, trailed by hypothetical examination. Mathematical investigation sets up the accuracy of the proposed calculations.

The ultimate goal of armour research is to create better armour for battle worthy combat plat forms such as main battle tanks, infantry combat vehicles and light combat vehicles. In each of these applications, the main aim boils down to one of the two things; either reduce the weight without sacrificing protection or enhance the performance at same or even reduced weight. In practice, these ambitions can be fulfilled only if we have with us, appropriate improved armour materials, advanced and innovative technologies and also improved designs, which enable us to use them for creating next generation armour modules. Armour systems have progressed through improvements in metallic, ceramic and lightweight (low areal density) composite materials. Similarly, the advances in development of explosive reactive armour (ERA) and non-explosive reactive armour (NERA) have generated efficient armour system against contemporary high explosive antitank ammunition and missile threats for the armoured vehicles. Yet, to achieve armour performance exceeding that of the current light combat vehicles and main battle tanks, further advancements in armour materials, systems, and survivability technologies are required for new vehicular systems that weigh significantly less than the present combat platforms. Various approaches and advancements in the metallic and composite armour materials, ERA and NERA systems to improve the survivability of armoured vehicles in the futuristic multi-spectral battlefield scenarios are described.

The Single Linear Induction Motor (SLIM) is a specialized electrical machine that produces linear motion instead of the rotary motion produced by a traditional rotary induction motor. SLIM's accurate dynamic model is required to analyze the performance of the motor under different operating conditions. Dynamic modelling of SLIM using the traditional DQ- axis equivalent circuits is difficult due to the time-varying parameters such as end effect, air gap flux, saturation, and half-filled slot. The two methods for modelling SLIMs were compared, namely the conventional method and the split method. The results of the comparison showed that both methods provided similar results, but the split method offered a more detailed analysis of the components and provided deeper insight into the behavior of the motor. The choice between the two methods depends on the specific requirements and objectives of the analysis. In this paper, the dynamic model of SLIM is modelled using conventional and split methods in MATLAB/SIMULINK. The results of the two modelling methods are compared with each other, and it is concluded that the splitting method provides better transient performance than traditional D-Q axis methods.

Normally speed control of a Single-Sided Linear Induction Motor (SLIM) by an indirect vector control scheme is difficult because the motor's parameters are time-dependent and the performance depends on various factors such as end effect, saturation, location of primary losses, and iron losses. Traditional PI current regulators are commonly used in vector regulators, but there is a tuning problem due to the oscillation of an operating point. This problem can be overcome by substituting an adaptive neuro-fuzzy-based current controller, and this controller improves the operation of a SLIM, such as its motor speed and thrust force. In this adaptive neuro-fuzzy controller, the ID and IQ errors and the error delay are inputs, and its outputs are Vds and Vqs, respectively. It is trained based on available values. A SLIM's dynamic modelling is implemented by dividing current (I) and flux-linkages into two terms. In these two terms, one is dependent on the end effect, and the other is independent of the end effect. The function of a Voltage Source Inverter (VSI)-fed indirect vector-controlled SLIM drive is simulated in MATLAB/Simulink, and its operation under various operating conditions is studied using an adaptive neuro-fuzzy current controller. These results are compared to a traditional P-I controller. The Pulse Width Modulation (PWM) technology that is used for controlling the VSI is called Space Vector Modulation (SVM).