Comparison of backstepping, sliding mode and PID regulators for a voltage inverter

<p><span>In the present paper, an efficient and performant nonlinear regulator is designed for the control of the pulse width modulation (PWM) voltage inverter that can be used in a standalone photovoltaic microgrid. The main objective of our control is to produce a sinusoidal voltage output signal with amplitude and frequency that are fixed by the reference signal for different loads including linear or nonlinear types. A comparative performance study of controllers based on linear and non-linear techniques such as backstepping, sliding mode, and proportional integral derivative (PID) is developed to ensure the best choice among these three types of controllers. The performance of the system is investigated and compared under various operating conditions by simulations in the MATLAB/Simulink environment to demonstrate the effectiveness of the control methods. Our investigation shows that the backstepping controller can give better performance than the sliding mode and PID controllers. The accuracy and efficiency of the proposed backstepping controller are verified experimentally in terms of tracking objectives.</span></p>

Segmentation Enhanced Elastic Image Registration for 2D Speckle Tracking Echocardiography—Performance Study In Silico

Although the two dimensional Speckle Tracking Echocardiography has gained a strong position among medical diagnostic techniques in cardiology, it still requires further developments to improve its repeatability and reliability. Few works have attempted to incorporate the left ventricle segmentation results in the process of displacements and strain estimation to improve its performance. We proposed the use of mask information as an additional penalty in the elastic image registration based displacements estimation. This approach was studied using a short axis view synthetic echocardiographic data, segmented using an active contour method. The obtained masks were distorted to a different degree, using different methods to assess the influence of the segmentation quality on the displacements and strain estimation process. The results of displacements and circumferential strain estimations show, that even though the method is dependent on the mask quality, the potential loss in accuracy due to the poor segmentation quality is much lower than the potential accuracy gain in cases where the segmentation performs well.

Analysis of the Effect of Employee Engagement, Perceived Organizational Support, and Motivation on Employee Performance Study at PT. Dino Jaya Karya

This research was conducted with the aim of knowing the effect of employee engagement, perceived organizational support, and motivation on the performance of employees of PT. Dino Jaya Karya. This research uses descriptive research with a quantitative approach. The data collection technique was carried out using a questionnaire media with the Likert method. The population in this study were 80 permanent employees of PT. Dino Jaya Karya. The sampling technique used is using a saturated sample (total sampling). The total sampling obtained is as many as 80 employees from PT. Dino Jaya Karya. The t test shows that the employee engagement variable (X1) has a positive and significant effect on the employee performance variable (Y) with a value of 0.000, the perceived organizational support variable (X2) has a positive and significant effect on employee performance ( Y) with a value of 0.000, and the motivation variable (X3 has a positive and significant effect on employee performance variable (y) with a value of 0.004. In the F test results employee engagement, perceived organizational support, and motivation have a simultaneous effect on employee performance as indicated by a significance value of 0.000. Keywords: Employee engagement, perceived organizational support, motivation, employee

A Comparative Performance Study of Classification Models for Opinion Mining

Opinion mining has become a major part in today's economy. People would want to know more about a product and the customers opinion before buying it. Companies would also want to know the opinions of the customers. Therefore, analyzing the customer’s opinion is important. A new customer would consider a product as good by analyzing the opinions of other customers. The opinions are collected from various areas, which include blogs, web forums, and product review sites. Classifying these large set of opinions requires a good classifier. In view of this, a comparative study of three classification techniques - Naive Bayes classifier with Kernel Density Estimation (KDE), Support Vector Machine (SVM), Decision Tree and KNN was made. To evaluate the classifier accuracy, precision, recall and F-measure techniques are used. Experimental results show that the Naive Bayes with Kernel Density Estimation (KDE) classifier achieved higher accuracy among others.

Acoustic Performance Study of Fiber-Optic Acoustic Sensors Based on Fabry–Pérot Etalons with Different Q Factors

The ideal development direction of the fiber-optic acoustic sensor (FOAS) is toward broadband, a high sensitivity and a large dynamic range. In order to further promote the acoustic detection potential of the Fabry–Pérot etalon (FPE)-based FOAS, it is of great significance to study the acoustic performance of the FOAS with the quality (Q) factor of FPE as the research objective. This is because the Q factor represents the storage capability and loss characteristic of the FPE. The three FOASs with different Q factors all achieve a broadband response from 20 Hz to 70 kHz with a flatness of ±2 dB, which is consistent with the theory that the frequency response of the FOAS is not affected by the Q factor. Moreover, the sensitivity of the FOAS is proportional to the Q factor. When the Q factor is 1.04×106, the sensitivity of the FOAS is as high as 526.8 mV/Pa. Meanwhile, the minimum detectable sound pressure of 347.33 μPa/Hz1/2 is achieved. Furthermore, with a Q factor of 0.27×106, the maximum detectable sound pressure and dynamic range are 152.32 dB and 107.2 dB, respectively, which is greatly improved compared with two other FOASs. Separately, the FOASs with different Q factors exhibit an excellent acoustic performance in weak sound detection and high sound pressure detection. Therefore, different acoustic detection requirements can be met by selecting the appropriate Q factor, which further broadens the application range and detection potential of FOASs.

Wearable Sensors Based on Force-Sensitive Resistors for Touch-Based Collaborative Digital Gaming

We report new classes of wearable sensors that monitor touch between fully-abled and disabled players in order to empower collaborative digital gaming between the two. Our approach relies on embroidered force-sensitive resistors (FSRs) embedded into armbands, which outperform the state-of-the-art in terms of sensitivity to low applied forces (0 to 5 N). Such low forces are of key significance to this application, given the diverse physical abilities of the players. With a focus on effective gameplay, we further explore the sensor’s touch-detection performance, study the effect of the armband fabric selection, and optimize the sensor’s placement upon the arm. Our results: (a) demonstrate a 4.4-times improvement in sensitivity to low forces compared to the most sensitive embroidered FSR reported to date, (b) confirm the sensor’s ability to empower touch-based collaborative digital gaming for individuals with diverse physical abilities, and (c) provide parametric studies for the future development of diverse sensing solutions and game applications.