Analog and Digital Speed Control of DC Drives Using Proportional-Integral and Integral-Proportional Control Techniques

A comparative study of proportional-integral (P-I) and integral-proportional (I-P) control schemes, for the speed control of a dc drive, using both analog-and microprocessor-based digital circuits, is presented. The often-neglected current response is discussed and results are presented. The speed response to step changes in speed reference and load torque, using both the control schemes, is compared to evaluate the merits of I-P control. A brief discussion of sensitivity to controller gains is also given. It is shown that the I-P control scheme offers some distinctive advantages over P-I control. Experimental and simulation results are also presented.     

Nanoglass–Nanocrystal Composite—a Novel Material Class for Enhanced Strength–Plasticity Synergy

The properties of a material can be engineered by manipulating its atomic and chemical architecture. Nanoglasses which have been recently invented and comprise nanosized glassy particles separated by amorphous interfaces, have shown promising properties. A potential way to exploit the structural benefits of nanoglasses and of nanocrystalline materials is to optimize the composition to obtain crystals forming within the glassy particles. Here, a metastable Fe‐10 at% Sc nanoglass is synthesized. A complex hierarchical microstructure is evidenced experimentally at the atomic scale. This bulk material comprises grains of a Fe₉₀Sc₁₀ amorphous matrix separated by an amorphous interfacial network enriched and likely stabilized by hydrogen, and property‐enhancing pure‐Fe nanocrystals self‐assembled within the matrix. This composite structure leads a yield strength above 2.5 GPa with an exceptional quasi‐homogeneous plastic flow of more than 60% in compression. This work opens new pathways to design materials with even superior properties.     

Microstructural and Mechanical Characterization of Two Aluminium Based In Situ Composite Foams

In situ composites are multiphase materials where the reinforcing phase is synthesized within the matrix during composite fabrication. The present paper deals with the processing, microstructural and mechanical characterization of Al?C7Si?C0.3Mg?C10TiB₂ and Al?C4Cu?C10TiB₂ foams. Composite foams with very low relative density (??_r?=?0.17?C0.37) and foams containing uniform cell sizes were successfully processed. Since the TiB₂ particle sizes are less than 2???m and have a good wetting behaviour, TiB₂ can be very good foam stabilizers. Microstructural characterization of the cell walls showed significant grain refinement since TiB₂ is a grain refiner. Elemental mapping clearly showed TiB₂ particles at inter dendritic boundaries. Compression testing of the processed foams showed some interesting features. Stress?Cstrain curve showed a lot of serrations which indicated brittle fracture of the cell walls and edges. Hence, it is observed that a balance should be attained between the grain refinement of ??-Al grains and the amount of TiB₂ particles to obtain desirable mechanical properties. Energy absorbed by the processed foams was calculated and they were observed to be close to that of the commercially available ALPORAS foams.     

An effective autism spectrum disorder screening method using machine learning classification techniques

Nowadays, autism spectrum disorder (ASD) is one of the fastest-growing developmental disorders globally. Screening test consumes more time and expensive to detect the autism signs. Due to advances in artificial intelligence and machine learning (ML), Autism can be predicted at the initial stage. Numerous researches have been conducted using different methods, but none of these researches presented any anticipated results about the capability to predict autism traits under different age groups. Therefore, this paper proposes an effectual prediction method based upon ML strategy to develop a mobile application for predicting ASD of any age people. The autism prediction model is developed by five ML classifiers, such as Gaussian Naive Bayes, Decision Tree Classifier, K-Nearest Neighbors (KNN), Multinomial Logistic Regression (MLR), Support Vector Machine (SVM) and also a mobile application is developed using proposed prediction method. The proposed method is analyzed with IAPQ records gathered from certain areas in Erode district, Tamil Nadu, India. From the analysis, the SVM classifier achieves maximum sensitivity of 23.14%, 6.04%, 5.89%, 11.03% than other classifiers, like Gaussian Naive Bayes, Decision Tree Classifier, KNN, and MLR.     

A comparative study of a Luenberger observer and adaptiveobserver-based variable structure speed control system using aself-controlled synchronous motor

An analysis of the state-observer-based robust speed control of a self-controlled synchronous motor (SCSM) is presented. A variable-structure control technique is utilized to achieve robust (parameter-insensitive) characteristics. The speed and acceleration signals required for the implementation of the variable-structure speed control (VSSC) are dynamically estimated with state observers. Two kinds of observers-the Luenberger full-order observer and an adaptive observer-are explored. The results obtained illustrate that Luenberger observers do not estimate the system states accurately when the system parameters vary. This inaccuracy in the state estimation results in a deterioration of the VSSC performance. Therefore, the possibility of using an adaptive state observer (ASO) is investigated. It is shown that the ASO estimates the system parameters and the system states simultaneously, thus making VSSC possible. The design methods and simulation results are presented to demonstrate the potential of the scheme     

Accessible-states-based sliding mode control of a variable speeddrive system

This paper presents a suitable control law and a novel method for the implementation of the sliding mode speed control (SLMSC) of a variable speed synchronous motor drive system. The analysis and results presented demonstrate that considerable simplification of design and circuit complexity can be achieved for SLMSC by employing the system states which are accessible or measurable. Both experimental and simulation results are presented to illustrate the potential of the proposed method     

Precipitation kinetics in Al-Si-Mg/TiB2 in-situ composites

Al-7Si-0.3Mg-TiB₂ in-situ composites were made by the salt-metal reaction i.e., the reaction of K₂TiF₆ and KBF₄ salts with the molten alloy. The kinetics of the formation of intermediate metastable precipitates in the process of Mg₂Si formation in Al-7Si-0.3Mg-TiB₂ in-situ composites with three different amounts of TiB₂ particles (2.5, 5 and 10 wt.%) were studied using differential scanning calorimeter (DSC) and also compared with the Al-7Si-0.3Mg base alloy. Kissinger analysis of non-isothermal DSC scans at various heating rates was carried out to evaluate the activation energies associated with the precipitation processes. The metastable precipitates were characterized by taking the solutionized samples to their respective DSC peak temperatures at a particular heating rate and the samples were then observed under a transmission electron microscopy. It was found that there is a decrease in the activation energies of the GP zones with increase in TiB₂ content.