System research and information technologies

Decentralized leader-following consensus control design for discrete-time multi-agent systems with switching topology

Yurii Dorofieiev — 2024-06-28

The problem of consensus control of linear discrete-time multi-agent systems (MASs) with switching topology is considered in the presence of a leader. The goal of consensus control is to bring the states of all agents to the leader state while providing stability for local agents, as well as the MAS as a whole. In contrast to the traditional approach, which uses the concept of an extended dynamic multi-agent system model and communication topology graph Laplacian, this paper proposes a decomposition approach, which provides a separate design of local controllers. The control law is chosen in the form of distributed feedback with discrete PID controllers. The problem of local controllers’ design is reduced to a set of semidefinite programming problems using the method of invariant ellipsoids. Sufficient conditions for agents’ stabilization and global consensus condition fulfillment are obtained using the linear matrix inequality technique. The availability of information about a finite set of possible configurations between agents allows us to design local controllers offline at the design stage. A numerical example demonstrates the effectiveness of the proposed approach.

Gradient projection: simplifying minimization area by affine transform

Igor Spectorsky — 2024-06-28

One of the classical problems of optimization theory in a finite-dimensional space is to find a minimum of a function on a nonempty set. Usually, finding the precise solution to this task analytically requires a lot of computational resources or is even impossible at all. So, approximate methods are used most often in practical cases. One of the simplest and the most well-known among such approximate methods for unconditional optimization is the method of gradient descent; its generalization for conditional optimization was found in 1964, the method of projected gradient. For some simple sets (line segment, parallelepiped, ball), the projection of the point on the set can be easily found by an explicit formula. However, for more complicated sets (e.g., an ellipse), projecting becomes a separate task. Nevertheless, sometimes computing projection can be simplified by affine transform; e.g., an ellipse can be transformed into a ball by affine (moreover, by linear) transformation. The paper aims to simplify the problem of minimizing function on the set by changing the condition set by affine transform F(x)= Ax+b, where A is a non-degenerated square matrix, and b is a fixed vector of proper dimension.

Study of the factor influence on the uniformity of coffee grain grinding by methods of statistical analysis

Ihor Hryhorenko — 2024-06-28

In order to assess the impact of each of the factors that affect the quality and uniformity of grinding coffee beans and to compare the impact of these factors, it is worth establishing a quantitative indicator of this impact. To solve this problem, dispersion analysis was used as a method of organizing sample data according to possible sources of dispersion. The chosen method made it possible to decompose the total dispersion into components caused by the influence of factor levels. Grinding time, geometric dimensions of the grain, moisture content of the grain, speed of rotation of the motor shaft were selected as factors influencing the homogeneity of grinding. The justification and assessment of the reliability of statistical conclusions about the informational significance of indicators affecting the homogeneity of coffee grinding was carried out to ensure the highest possible probability of the obtained result.

An improved approach to organising mobile edge computing in a 5G network

Andrii Astrakhantsev — 2024-06-28

Mobile edge computing is an important element in ensuring the efficiency of the 5G network as a whole, as it enables data storage and computing at the network edge. Existing solutions do not fully address the issues of load distribution between computing nodes, and most solutions do not offer methods for verifying computations and controlling errors. Accordingly, this paper aims to develop an approach to the organization of mobile edge computing in a 5G mobile network that would authenticate distribution servers and computing nodes, manage the process of distributing computing nodes, have a procedure for verifying the correctness of calculations, and take into account the parameters of computing nodes during distribution. To achieve this goal, we propose to use the developed method. The method of load balancing and selection of computing nodes for edge computing via 5G allows for identifying available nodes and distributing computing blocks among them. It also provides mutual authentication of elements and includes a method of data verification and error detection for the MEC system. The provided solution allows for controlling errors during calculations and protecting the server from incorrect data. These methods are optimized according to minimum network resources and computing time criteria. These improvements increase the efficiency of mobile edge computing in a 5G network.

Expansion of the mathematical apparatus of discrete-continuous networks for the automation of their synthesis procedures

Alexander Gurskiy — 2024-06-28

The paper deals with a model of an intelligent system related to the automatic synthesis of Petri nets and presents a certain stage of developing this model. The peculiarity of the extended mathematical apparatus is that it contains a combination of Petri net incidence matrices to represent various algorithms. This combination of matrices is part of the equations describing the logic control device of a complex system. Accordingly, the work also presents a well-known mathematical description of discrete-continuous systems with a controlled structure, which includes certain logical control devices. This mathematical description, based on means of discrete-continuous networks, is associated with the incidence matrix of the Petri net, which is formed as a result of a particular synthesis algorithm. At the same time, the formed Petri net represents the corresponding logical control algorithm that should ensure the effective functioning of the corresponding system. The final part of the work presents various structural schemes of logic-dynamic models of systems related to the automatic synthesis of Petri nets. Here, we determine the features of the advanced mathematical apparatus based on discrete-continuous networks to develop an intelligent system that forms logical control algorithms. It is also noted that such systems can be used to create certain control algorithms that ensure increased efficiency of the functioning of some objects in difficult and unpredictable conditions.

A hybrid model of artificial intelligence integrated into GIS for predicting accidents in water supply networks

Yuriy Zaychenko — 2024-06-28

The search for an effective and reliable model for predicting accidents on water supply networks by determining their exact locations has always been important for effectively managing water distribution systems. This study, based on the adaptive neuro-fuzzy logical inference system (ANFIS) model, was developed to predict accidents in the city of Kyiv (Ukraine) water supply network. The ANFIS model was combined with genetic algorithms and swarm optimization (ACO) methods and integrated into a GIS to visualize results and determine locations. Forecasts were evaluated according to the following criteria: mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Depending on the amount and type of input data, ANFIS optimization with genetic algorithms and swarm optimization (ACO) can, on average, increase the accuracy of ANFIS predictions by 10.1% to 11%. The obtained results indicate that the developed hybrid model may be successfully applied to predict accidents on water supply networks.

Interactive decision support system for lung cancer segmentation

Volodymyr Sydorskyi — 2024-06-28

This paper studies Clinical Intelligent Decision Support Systems (CIDSSs) for lung cancer segmentation, which are based on deep neural nets. A new interactive CIDSS is proposed and compared with previous approaches. Additionally, the purpose uncertainty problem in building interactive systems is discussed, and criteria for measuring both quality and amount of user feedback are proposed. In order to automate system evaluation, a new algorithm was used to simulate expert feedback. The proposed interactive CIDSS outperforms previous approaches (both interactive and noninteractive) on the task of lung lesion segmentation. This approach looks promising both in terms of quality and expert user experience. At the same time, this paper discusses a bunch of possible modifications that can be done to improve both evaluation criteria and proposed CIDSS in future works.

Strategy of the cyber-physical system for the small business enterprise guaranteed functioning with the digital twin support

Nataliya Pankratova — 2024-06-28

The article presents a strategy of the cyber-physical system guaranteed functioning for a small business enterprise (SBE), which is ensured by maintaining the digital twin and is due to its extremely high relevance in modern conditions. Business processes are linked to Industry 4.0 competencies. One of the innovations it implements is Digital Twin, a comprehensive facility support tool. Digital twin allows for tracking and effectively managing the entire cycle of an infrastructure project, from planning, procurement, and production to commissioning and maintenance of the facility. PEST, SWOT, SAW, TOPSIS, and VIKOR methods are used to build a strategy.

Multi-factor forecasting of statistical trends for data science problems

Oleksii Pysarchuk — 2024-06-28

The article deals with the processes of multi-factor forecasting of statistical trends for Data Science problems. Most of the classic approaches to data processing consist of studying the consequences of phenomena rather than the factors of their appearance. At the same time, the factors affecting the behavior of the investigated process are assumed to be random and are not investigated. The article discusses the approach to forecasting the parameters of the trend of statistical time series, which consists of the study of factors that lead to changes in the dynamics of the studied process. This approach potentially has better indicators of adequacy, accuracy, and efficiency in obtaining final solutions than classical approaches. The implementation of this approach is shown using an example of the analysis of exchange rate changes. The obtained results show the practicality of considering multi-factoriality in forecasting tasks.

Polarization-based target detection approach to enhance small surface object identification ensuring navigation safety

Maksym Stetsenko — 2024-06-28

This research introduces a groundbreaking approach to significantly enhance the performance of navigation radars under adverse weather conditions. Traditional ship radars, relying on horizontal polarization, encounter difficulties in effectively suppressing rain interference. In response, this study proposed an innovative method employing circular polarization for detecting navigation targets. This technique capitalizes on the distinct polarization properties exhibited by stable navigation targets and fluctuating interfering objects. Theoretical analysis and model experiments substantiate consistent ellipticity parameter values of scattered waves, independent of rain intensity, for both rain interferers and surface metallic objects. The practical implications of our research are highly promising. They enable detection irrespective of the noise-to-signal ratio by integrating an additional channel of circularly polarized waves and applying straightforward mathematical functions. This advancement marks a significant stride towards overcoming the challenges posed by rainy conditions in maritime navigation radar systems.