This paper presents some novel force ripple reducing techniques for tubular permanentmagnet linear machines (TPMLMs) with the square-shaped cross section. These methods are very straightforward, so their implementation in TPMLMs with the square cross section is easy. An analytical form of machine parameters such as the thrust force is obtained by solving the analytical field. A modular configuration for permanent-magnet pole is used to reduce teeth cogging force. Furthermore, the manufacturing cost of TPMLMs can be reduced by using modular pole permanent-magnet. In this method, the width of permanent-magnets (PMs) is calculated by using Fourier analysis and a sensitivity analysis has been conducted to identify the robustness of this technique. Additional stator side methods are used to decrease the end face cogging force. Moreover, the stator teeth shifting method is proposed to reduce the electromagnetic force ripples. Also, the produced electromagnetic force of the machine is increased by using a delay in the power supply. 3 − D non-linear finite-element analyses and experimental tests are performed to investigate the effectiveness and performance of proposed techniques.

This paper introduces a two-dimensional autonomous mega-stable dynamical system with trigonometric nonlinearities. The nonlinearity of this system is induced by tangent hyperbolic and cosine functions. A remarkable feature of this system is the ability to generate very rich patterns of coexisting attractors via the variation of its parameters. Interestingly the shapes of its coexisting attractors resemble some real-life objects, such as Persian rugs, nuts (mainly chestnut), fruits (especially pear), and vegetables (pumpkin and onion). Simulations demonstrate the coexisting attractors, basins of attractions, and real-life object shapes. Moreover, the fixed points of the proposed system, their stability, and the energy dissipation for various pairs of parameters are investigated. Finally, the feasibility of this system is approved by analog circuit simulations. Regarding the high flexibility of this system, producing a broad range of attractor patterns, it could be applied in various fields.

Variable reluctance energy harvester (VREH) is a good candidate of transducers to transform the environmental energy into electricity. VREHs act based on electromagnetic induction due to the variation of air-gap reluctance with the rotation of wheel. This paper presents an accurate analytical model based on magnetic equivalent circuit (MEC) model and conformal mappings (CMs) for electromagnetic modeling the VREHs, which have a large air-gap. The geometry of analyzed VREH on both sides of air-gap including the iron parts, slots, and permanent magnets (PMs) is divided into many elements in cylindrical coordinate, and each element is then replaced with an equivalent permeance model. The air-gap region is modeled with permeances calculated by the CM method, which can accurately consider the real paths of flux tubes in large air-gap. The obtained air-gap permeances are then used in MEC model for electromagnetic modeling and analysis of studied VREH, while considering the effects of slots and magnetic saturation, accurately. In final, the analytical results are verified by comparing with the corresponding results obtained through finite element method (FEM).

The coronavirus spread rapidly in the world and caused the disease of Covid-19. The proposed research was conducted with the aim of classifying people with Covid-19 from other people. lung ultrasound images were used to diagnose covid-19. The open source Point-Care-of-Ultrasound (POCUS) database was collected, which contained 59 Lung Ultrasound (LUS) images and was collected from several other databases. In this research, KNN classifier with K-fold cross validation was used to classify the feature matrix obtained from Fractional B-spline Wavelet Transform (FBSWT). The proposed method, Block-Matching and 3D filtering (BM3D) filter was used in some methods, which had acceptable results. The proposed method was used to classify healthy people from patients with Covid-19. The results show that when the features based on the wavelet transform (WT) are used, the proposed method can be achieved 90.90% sensitivity, 92.30% specificity, and 91.42% accuracy. While the features extracted from FBSWT show that the proposed method can be achieved 95.45% sensitivity, 93.30% specificity, and 94.28% accuracy. Fractional transforms, especially the FBSWT, can be a useful tool for image processing. They can be used for various purposes such as detection and classification. By using FBSWT, it is possible to accurately diagnose the disease of covid-19.

The method of Mono-Inverter Dual-Parallel (MIDP) motors has been noticed in the drive of the multimotor systems in order to reduce the number of power electronic devices as well as the volume, weight, and cost of the drive system. The load torque imbalance in motors has been one of the main problems of these systems because of feeding the motors by a single inverter. Some control methods have also been proposed in this field and studies are ongoing. This paper deals with an effective Model Predictive Control (MPC) method for the design of speed and current controllers in MIDP motors. Pontryagin's Maximum Principle and the Lagrange method are used in designing the current and speed controllers respectively. The current controller generates control signals as linearparametric functions through the offline solving of the quadratic-linear cost function. Instead of using conventional PI controllers in the speed control loop, speed controllers are designed based on the regulating kinetic energy of motors. After driving and simplifying the mathematical equations, the proposed method is simulated. Simulation results are compared with Finite Control Set-MPC. These results validate the prompt and accurate performance of proposed controllers in transient and steady states.

In this article the complex dynamics of a laser model, which externally injected class 𝐵 which is described by a system of three nonlinear ordinary differential equations with two parameters for field intensity phase and population inversion, are studied. In particular, we investigate the integrability and nonintegrabilty of laser system in three dimension. We prove that system is completely integrable only when the parameters are zero. Particularly, we study polynomial, rational, Darboux and analytic first integrals of the mentioned system. Moreover, we compute all the invariant algebraic surfaces and exponential factors of this system. We find sufficient conditions for the existence of periodic orbits emanating from an equilibrium point origin of a laser differential system with a first integral.

The metal hydride tube used to store the hydrogen needs to be heated to remove the moisture inside and allow the hydrogen to flow out in it. Instead of conventional heating methods, the induction heating method is used to heat the metal hydride tube in this study. Class-E inverter constitutes the power stage of the system because of its simple structure, easy applicability, and low cost. The power switch of the inverter is driven with hybrid control, in which Frequency Modulation (FM) and Pulse Density Modulation (PDM) techniques are used together. Thus, the situations where one of the techniques is more advantageous than the other are utilized. Moreover, the positive aspects of each technique are highlighted. Fuzzy Logic Controller (FLC), which is independent of changing system parameters, carries out the power control of the inverter. A prototype of 232 W system consisting of the power and control circuit is established to verify the theoretical analysis and functionality of the hybrid control. To fix the tube temperature to the reference temperature of 250 °C, the system is controlled in a closed-loop with FM-PDM-based FLC in the switching frequency range of 25-35 kHz. Highly efficient power control is carried out with FM-PDM-based FLC in a wide range.

Statistical process control provides various types of control charts for monitoring of mean and variance shifts in the industrial production process individually as well as jointly to improve and maintain the quality products. The authors proposed these control charts based on sample values selected to calculate the desired statistics assuming that these values are measured correctly. But in a real life situation, measurements of the values may suffer from errors ultimately affecting the efficiency of the control charts. A few of the researchers in the field of control charts also discussed the problem of measurement error during process monitoring and proposed solutions to avoid losses of producers. We also present a hybrid exponentially weighted moving average control chart for joint monitoring of mean as well as variance and study the effect of measurement error on the efficiency of this control chart and name it as Max-HEWMAME control chart. The impact of measurement error has been shown in the calculations and presented in the shape of average run lengths ( ) and standard deviations of run lengths ( ) using the Monte Carlo simulation method. A real life example is also included to support the simulation results.

In this research, a bidding problem for a wind-power plant participating in a day-ahead power market with uncertain correlated market prices is studied. A new robust optimization approach considering correlation among uncertainty on the hourly prices in a day-ahead market is developed. This results in solutions with lower level of over-conservatism. For this purpose a new correlated polyhedral uncertainty set is introduced. To consider the uncertainty of market clearing prices and the value of power produced by wind power producer a bidding algorithm is developed. Results of the study using a robust modelling the bidding problem reveal that the appliance of the proposed model on the bidding problem for a price-taker wind power plant in a day-ahead market with uncertain correlated data leads to solutions with superior performance than that of the conventional polyhedral uncertainty sets.