Observation of charge ordering signal in monovalent doped Nd0.75Na0.25-xKxMn1O3 (0 ≤ x ≤ 0.10) manganites

K doping in the compound of Nd0.75Na0.25-xKxMn1O3 (x = 0, 0.05 and 0.10) manganites have been investigated to study its effect on crystalline phase and surface morphology as well as electrical transport and magnetic properties. The structure properties of the Nd0.75Na0.25- xKxMnO3 manganite have been characterized using X-ray diffraction measurement and it proved that the crystalline phase of samples were essentially single phased and indexed as orthorhombic structure with space group of Pnma. The morphological study from scanning electron microscope showed there was an improvement on the grains boundaries and sizes as well as the compactness with K doping suggestively due to the difference of ionic radius. On the other hand, DC electrical resistivity measurement showed all samples exhibit insulating behavior. However, analysis of dlnρ/dT-1 vs. T revealed the clearly peaks could be observed at temperature 210K for x = 0 and the peaks were shifted to the lower temperature around 190 K and 165 K for x = 0.05 and x = 0.1 respectively, indicate the existence of charge ordering (CO) state in the compound. Meanwhile, the investigation on magnetic behavior showed all samples exhibit transition from paramagnetic phase to anti-ferromagnetic phase with decreasing temperature and the TN was observed to shift to lower temperature suggestively due to weakening of CO stat

Evolution of Controllers for the Speed Control in Thyristor Fed Induction Motor Drive

Induction Motors (IMs) are now becoming the pillar of almost all the motoring applications related to the industry and household. The practical applications of IMs usually require constant motoring speed. As a result, different types of control systems for IM's speed controlling have been shaped. One of the important techniques is the utilization of thyristor fed drive. Although, the thyristor fed induction motor drive (TFIMD) offers stable speed performance, the practical speed control demand is much more precise. Hence, this drive system utilizes additional controllers to attain precise speed for practical applications. This paper offers a detailed review of the controllers utilized with the thyristor fed IM drive in the past few decades to achieve good speed control performance. The clear intent of the paper is to provide a comprehensible frame of the pros and cons of the existing controllers developed for the TFIMD speed control requirements. Keywords: Thyristor Fed Drives, Induction Motors, Speed Controller, Conventional Controllers, and Soft Computing Techniques

Comparative analysis of PID and neural network controllers for improving starting torque of wound rotor induction motor

Unlike 3-phase squirrel cage induction motor, starting-up of 3-phase wound rotor counter part can be improved by adding an external resistance to the rotor circuit.Thus, leads to reduce starting current and increase starting torque. In this paper two controllers for 3-phase wound rotor induction motor have been proposed include conventional proportional integral derivative (PID)  controller and the other based on artificial neural network (NARMA-L2). A comparison between these controllers has been conducted. It has been shown that starting torque of the motor has been improved, when utilizing the neural network controller compared to the conventional counter  part. It should be noted that MATLAB/SIMULINK has been used to implement both controllers

The use of microorganisms in dairy products (butter)

Butter is widely used in cooking and baking, particularly by those who enjoy cakes and sweets. Butter is categorized as a dairy product which is made from fat and protein. Biotechnology knowledge is applied in the process of making butter because it involves microorganisms such as bacteria, yeast, fungi, marine diatoms and protozoa. The steps in the process of making butter include separating raw milk, skim, pasteurization, storage, evaporation, and drying. The neutralization of butter cream is vital in lowering the acidity of cream, which prevents unpleasant odors

Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

A New Modified MPPT Controller for Indirect Vector Controlled Induction Motor Drive with Variable Irradiance and Variable Temperature

Due to the increase in power demand and the earth natural resources are depleting day by day, renewable energy sources have become an important alternate and solar energy is mainly used. In order to track the radiations from the sun in an efficient manner the maximum power point tracking (MPPT) controller is used. But the existed MPPT controllers were developed based upon the ideal characteristics of constant irradiation and temperature. To overcome the above problem a practical data is considered for designing of MPPT controller which is based upon variable irradiance under various temperatures. The output obtained from the MPPT is given to the boost converter with an inverter to find the performance of an indirect vector controlled induction motor drive under different operating conditions. For inverter control, a SVM algorithm in which the calculation of switching times proportional to the instantaneous values of the reference phase voltage. It eliminates the calculation of sector and angle information. The torque ripple and the performance of induction motor drive with ideal and practical data MPPT controllers are compared under different operating conditions. An experimental validation is carried out and the comparison is made with the simulation results. Keywords: maximum power point tracking, variable irradiance, indirect vector controlled, total harmonic distortions, space vector modulation, induction motor drive and torque ripple

Speed controller design for three-phase induction motor based on dynamic adjustment grasshopper optimization algorithm

Three-phase induction motor (TIM) is widely used in industrial application like paper mills, water treatment and sewage plants in the urban area. In these applications, the speed of TIM is very important that should be not varying with applied load torque. In this study, direct on line (DOL) motor starting without controller is modelled to evaluate the motor response when connected directly to main supply. Conventional PI controller for stator direct current and stator quadrature current of induction motor are designed as an inner loop controller as well as a second conventional PI controller is designed in the outer loop for controlling the TIM speed. Proposed combined PI-lead (CPIL) controllers for inner and outer loops are designed to improve the overall performance of the TIM as compared with the conventional controller. In this paper, dynamic adjustment grasshopper optimization algorithm (DAGOA) is proposed for tuning the proposed controller of the system. Numerical results based on well-selected test function demonstrate that DAGOA has a better performance in terms of speed of convergence, solution accuracy and reliability than SGOA. The study results revealed that the currents and speed of TIM system using CPIL-DAGOA are faster than system using conventional PI and CPIL controllers tuned by SGOA. Moreover, the speed controller of TIM system with CPIL controlling scheme based on DAGOA reached the steady state faster than others when applied load torque

Computational Intelligence Application in Electrical Engineering

The Special Issue "Computational Intelligence Application in Electrical Engineering" deals with the application of computational intelligence techniques in various areas of electrical engineering. The topics of computational intelligence applications in smart power grid optimization, power distribution system protection, and electrical machine design and control optimization are presented in the Special Issue. The co-simulation approach to metaheuristic optimization methods and simulation tools for a power system analysis are also presented. The main computational intelligence techniques, evolutionary optimization, fuzzy inference system, and an artificial neural network are used in the research presented in the Special Issue. The articles published in this issue present the recent trends in computational intelligence applications in the areas of electrical engineering

Fuzzy-based estimation of reference flux, reference torque and sector rotation for performance improvement of DTC-IM drive

In this study, the fuzzy-based reference flux estimator (RFE), reference torque estimator (RTE) and sector rotation strategy called fuzzy logic estimator are proposed to direct torque control of induction motor (DTC-IM) drive for performance improvement. The basic DTC-IM drive with conventional RFE, RTE and sector division causes large torque ripple, variable switching frequency and uneven voltage vector contribution in stator flux. The torque and speed responses of the proposed system are investigated with load variations. The simulation results of the proposed DTC-IM drive are compared with the basic DTC-IM drive. The assessment of the proposed system shows improved performance. A hardware is developed using Xilinx Spartan-6XC6SLX45-Field Programmable Gate Array (FPGA) Kit for experimental verification of the results. Moreover, sinusoidal pulse width modulation and space vector pulse width modulation techniques are applied to reduce the torque ripples. The performance of the drive is investigated for various speed ranges. The comparison of the simulated and experimental results proves that the proposed fuzzy-based DTC-IM drive provides better performance than the basic DTC-IM drive