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With shorter wavelengths than microwaves and greater penetration depth than infrared light, waves in the terahertz spectrum offer unique material testing opportunities. Terahertz technology offers non-invasive and non-destructive testing in the form of spectroscopy and imaging. The most used systems for terahertz imaging are time-domain spectroscopy systems. However, frequency domain spectroscopy systems could offer excellent frequency resolution and be more suitable for biomedical applications. Terahertz imaging based on frequency domain spectroscopy systems is slow, and suffers from frequency tuning errors. A novel one-dimensional imaging principle is presented in this paper. In addition, frequency range optimization based on convolutional neural networks and occlusion sensitivity is utilized for frequency range optimization. Frequency range optimization is used to determine the optimal frequency range for data acquisition. The optimal frequency range or bandwidth should be wide enough for effective phase detection, and should be at the intersection of several spectral footprints in the observed medium. The intersection of spectral footprints is estimated using the proposed frequency range optimization algorithm based on a convolutional neural network and occlusion sensitivity algorithm. The proposed algorithm selects the most sensitive frequency band of THz spectrum automatically, and enables very fast acquisitions for object inspection and classification.

The paper presents a modified adaptation algorithm for the super-twisted sliding mode controller structure, based on the barrier function method. The aim of the paper is to reduce the chattering phenomena of the controller, which limited the use of the controller in different applications. The chattering phenomena are mostly caused by the overestimated controller gain due to the assumed disturbance bound, which is mostly inaccurate. The chattering origins are also the unknown parasitic dynamic of the system and discrete implementation of the controller. The proposed method with the Barrier function is used to alleviate the chattering phenomena with the adaptation of the controller parameters. The novelty of the method is using an adaptation procedure only in prescribed regions of the sliding variable, otherwise, the adaptation is not used. The advantage of the method is the proper rejection of the chattering phenomena in the vicinity of the manifold of the sliding variable, regardless of the order of the system. With proper selection of the adaptation boundary, the effect of discrete implementation, especially for a longer sampling time of the algorithm, can be suppressed efficiently, as well as the effect of the overestimated controller parameters. The proposed method is verified and compared with a standard version of the algorithm in simulation and real-time environments.

This paper discusses nonlinear controller structure design for a synchronous reluctance motor (SynRM). The SynRM is represented with a nonlinear dynamic model. All presented nonlinearities of the SynRM are respected in the controller design procedure. A nonlinear controller policy is used for a SynRM positing system. The nonlinear controller design is based on the chattering alleviation technique for the super-twisted algorithm (STA). The alleviation technique assumes the presence of a fast parasitic dynamic, or fast, actuator. Based on the motor structure, the STA controller is designed only for the mechanical subsystem, where the electrical part presents the parasitic dynamic, and is taken in to account in the chattering suppression procedure. Chattering rejection is based on the STA describing function and harmonic balance equation. The approach allows determination of fast oscillation parameters, such as amplitude and frequency of oscillation. The conditions for the controller parameters’ selection are derived with regard to the given oscillation parameters. The derived conditions cover the stability analysis for the STA controller, as well as the stability condition for current controllers and chattering amplitude minimization. The result is confirmed with an example.

The constant development in ICT has not omitted the field of learning activities, digitalizing the concept of learning and making it more effective. This became even more obvious during the Covid-19 Pandemic when all educational activities were forced to be transferred remotely and online, with the help of existing Learning Management Systems. Motivated by this, the paper focuses on reviewing different LMSs and comparing their capabilities towards implementation of remote and virtual laboratories, providing analytical and empirical investigations. The goal is to assess the possibility of implementation and deployment of remote access, firstly to some existing on-campus laboratories hosting lab exercises based on real hardware; and secondly to virtual software platforms also usually available in the laboratories. Using such a set up enables the students to get the look and feel of what it means to be in presence in a real lab, nevertheless virtually. This immersive remote lab experience shall hereby be integrated into an already existing and widely used LMS for better operability and manageability. This work has been done in the course of the European project UbiLab (”A ubiquitous virtual laboratory framework”), conducted jointly between the Ss. Cyrill and Methodius University in Skopje, North Macedonia, Anhalt University, Koethen, Germany, and University of Maribor, Slovenia. In the course of the project a remote collaboration platform for hardware-in-the loop will be developed and deployed, and at the same time learning experience in using it in the course of the education process of electrical, system automation, and computer engineers shall be gathered. As an outcome of the work done, it was found that there is no ready-made solution for carrying out remote laboratory work that completely covers the goals of the UbiLab project. Thus, a custom solution based on the compilation of listed platforms components should be developed.