As the future electric power grid will be driven by distributed renewable energy sources, the deployment of grid-connected power converters will also grow to enable seamless grid and energy source interaction. To provide the reliable operation of these converters, the estimation of fundamental grid parameters is important. The most common estimation techniques are a phase-locked loops (PLL) and a frequency-locked loops (FLL). However, those techniques encounter challenges in conducting parameter estimation when the input signal is unbalanced due to DC-offset, harmonics, signal sags, and frequency and phase variations. This paper presents an enhanced FLL loop enriched with an additional loop for estimation and rejection of the DC-offset. Active and reactive power calculations in grid-connected microgrids by using the modified FLL loops with DC-offset rejection is a novel application introduced in this paper. Experimental verification has demonstrated that the enhanced FLL loop provides fast and reliable parameter estimation as well as stable and robust power calculations, even in the presence of a DC-offset.

For many years now MATLAB has been considered the academia standard when it comes to technical computing and simulation. Many university and college courses rely on multiple tool-boxes and ad-dons that MATLAB provides. With its relatively simple syntax, and large user community it has been, for so many years, a logical choice for academia. However, more often than not, students fresh out of university have been facing a new software that has very quickly become an industry standard in many areas of electrical engineering. On a simple example of DC motor control, this paper aims to showcase advantages of early adoption and using LabViewfor programming and simulation purposes in academia.

This paper presents the implementation of the Binary Search Algorithm (BSA) to determine the Maximum Power Point (MPP) of a photovoltaic (PV) system under variable weather conditions. Additionally, the conventional well-known Perturb and Observe (P&O) algorithm is also implemented to be compared with the binary search based Maximum Power Point Tracking (MPPT) algorithm. Both algorithms are implemented in real time in MATLAB/Simulink environment. The experimental study is performed using the two 260 W series connected PV modules, the buck converter, and Humusoft MF 634 card to enable real-time operation. The value of the duty cycle for the buck converter is being updated in each step moving the operation point closer to MPP. The obtained experimental results demonstrate that the binary search based MPPT algorithm is more efficient and accurate when compared to the P&O MPPT algorithm.

Gesture recognition is a field of study that involves recognizing human movements and gestures through sensors. In this paper, a basic gesture recognition system is proposed that uses three Time-of-Flight (TOF) VL53L0X distance sensors positioned in an L-shape able to recognize gesture through cover glass and up to 40 cm of distance. The system is capable of recognizing four basic gestures: swipe right, swipe left, swipe up and swipe down. This system can be applied in various fields such as Human-Computer Interaction (HCI), Gaming, Virtual Reality (VR) and Robotics, this paper will focus on the implementation and evaluation of the proposed system. The inspiration for the system is to simplify interaction with medical panel PCs and monitors while improving the hygienic aspect of the same, while taking into consideration data privacy.

Solar Particle Events (SPEs) generate cosmic radiation of different magnitude in a time span of several hours or even days. This contributes to an increased probability of higher magnitude Single-Event Upsets (SEUs) occurrence in space applications. It is critical to establish early detection of SEU rate or Soft Error Rate (SRE) changes to enable timely radiation hardening measures. This research paper focuses on the high-accuracy detection of SPEs using the manually collected space data. Additionally, the prediction of SRE increase or decrease was established with the seven widely used supervised machine learning algorithms. Excellent performance of 97.82%, including a high F1-score, was achieved during the presence of SPE using $k$-Nearest Neighbor algorithms.

The goal of this article is to describe a power measuring system using the frequency-locked-loop (FLL). The FLLs have a wide variety of applications such as power converters, grid synchronization, sensorless flux estimation and control of motor drives. This nature of the FLL system allows for it to be a potentially perfect tool for power calculation. In this article, a new power calculation method has been presented. This method is based on FLL as part of phase locked loop (PLL) and has enhanced feature over classical methods for power calculation widely used in industry. The obtained results showcase the effectiveness of the proposed FLL power calculation method.

This paper is focused on investigating a new approach for collecting the data about robot’s position and orientation from the RoboDK software in which the robot’s movement is simulated. The code, as well as the GUI (Graphical User Interface) was developed using MATLAB environment and connection between the two software packages was achieved through the TCP (Transmission Control Protocol) internet protocol. Robot model used for this purpose is the Unimation’s PUMA 560 industrial robot which can be found in the online library of the RoboDK. Information regarding robot joint angles is important for planning the robot’s movement and generating the trajectory between the two positions, so it could be of use to have all the position/orientation vectors listed for further calculations. Drawback of the RoboDK software is the inability to generate the trajectory so the goal of this project is to avoid that problem with the help of the MATLAB software.

The fast pace of scientific and technological developments and the pressing need for a flexible skilled workforce and innovative products in the more competitive than ever world markets require robust but flexible mechanisms for the development, implementation, monitoring and assessment of undergraduate and graduate curricula and courses. In our research, we focus on the quality assurance process designed to achieve the desired Learning Outcomes (LOs) for new courses and education programs. We propose tools and techniques used to determine the extent to which the stated learning outcomes are achieved. More specifically, we present the Quality Assurance approach developed in the ERASMUS+ CBHE project Electrical Energy Markets and Engineering Education (ELEMEND). The approach for developing the LOs is based on the European Qualification Framework (EQF) which defines professional levels in terms of learning outcomes, i.e. knowledge, skills and autonomy-responsibility, and the ENQA European Standards and Guidelines for determining the quality assurance procedures and metrics. As a case study, the methodology is applied to the LOs of ELEMEND courses and the results are discussed. Additionally, this paper reflects the unique experience of collaboration between EU universities, HEIs of West Balkans, enterprises, and professional associations in order to create up to date curricula in smart grid related topics with sustainable links to the related industry and businesses.