Search

Search Results

• MODEL OF COOPERATIVE TRANSPORTATION TASK ALLOCATION FOR HETEROGENEOUS ROBOTIC SYSTEMS

  S. Gong

  220-232

  2026-07-07

  Abstract ▼

  The development of intelligent warehouse systems and the automation of logistics processes require effective solutions for task allocation in heterogeneous multi-robot complexes, particularly in the cooperative transportation of large and heavy cargo. The aim of this work is to develop and verify a hybrid model for cooperative transportation task (CTT) identification and allocation in a warehouse environment, taking into account multi-criteria optimization. A brief review of publications on the application of mivar technologies and machine learning methods in the mathematical modeling of complex robotic systems is provided. A two-level approach is proposed, including a mivar decision-making system for the automatic identification of CTT and a task allocation model based on a combined auction algorithm. The required number of transport robots (RT) is determined by the mivar decision-making system, considering the size and mass of the cargo. The developed mathematical model for CTT allocation aims to improve efficiency and reliability by accounting for key dynamic factors (heterogeneity, redundancy, and path-dependent costs). Simulation experiments with 30 transport robots and 100 tasks demonstrated the superiority of the proposed method over baseline strategies (Random, Nearest Neighbor, Greedy Capacity): when processing 6 CTT, the total cost reduction reached up to 40.7%, and with 12 tasks, an additional reduction of 10.8% was achieved while maintaining 100% success rate. The model’s ability to scale efficiently was established, manifesting in an additional cost reduction of 10.8% as the number of tasks increased. The results indicate the robustness, adaptability, and high practical applicability of the model for integration into modern intelligent warehouse systems that handle a diversified range of cargo

• ANALYSIS OF THE EFFECTIVENESS OF TRADITIONAL AND MODERN TECHNOLOGIES FOR MONITORING POWER TRANSMISSION LINES

  О. V. Afanaseva , Т.F. Tulyakov

  182-188

  2025-10-01

  Abstract ▼

  The article provides a comprehensive analysis of the effectiveness of traditional and modern technologies for monitoring power transmission lines (PTL). Power transmission lines are a critical element of the energy infrastructure, and their reliable operation directly affects economic stability and safety. Traditional monitoring methods, such as visual inspections and mechanical devices, have long remained the main control tools, but their limited accuracy, high dependence on the human factor and the inability to promptly detect hidden defects make them less effective in the face of increasing loads on power systems. Modern technologies, including unmanned aerial vehicles (UAVs), the Internet of Things (IoT), automated monitoring systems and digital twins, offer fundamentally new opportunities for monitoring the condition of PTLs. They provide high diagnostic accuracy, continuous data collection in real time, reduced operating costs and increased personnel safety. The article presents a classification of both traditional and modern methods, as well as a comparative analysis of their key parameters: accuracy, response speed, cost, safety and impact on operation. The results of the study demonstrate that modern technologies outperform traditional approaches in all the criteria considered. In particular, the use of IoT and UAVs allows minimizing the human factor, reducing inspection time and increasing data detail. Digital twin systems make it possible to predict possible accidents and optimize scheduled maintenance. However, successful implementation of innovative solutions requires additional investment, personnel training and integration with existing management systems. The conclusion is made about the strategic importance of switching to modern power transmission line monitoring technologies to improve the reliability and sustainability of the energy infrastructure. Despite high initial costs, their long-term benefits, including reduced accidents, resource savings and increased safety, fully justify the investment. The authors emphasize the need for further development of digital technologies in the energy sector to ensure stable and efficient operation of power grids

• FEATURES OF LOW-VOLTAGE DIGITAL CIRCUITS BASED ON CMOS TECHNOLOGIES 90–20 NM

  B.G. Konoplev

  174-181

  2025-10-01

  Abstract ▼

  To increase energy efficiency, CMOS integrated circuits use a subthreshold mode of operation.
  The supply voltage decreases to a level lower than the threshold voltages of the MOSFETs, currents decrease and performance decreases. However, often a reduction in power consumption is more important than low performance. Therefore, CMOS integrated circuits in the subthreshold mode have applications where a radical reduction in power consumption is a crucial requirement. Now firms have used technologies with minimum sizes from 500 to 3 nm, with most of the products being at the 90–20 nm. The paper analyzes low-voltage circuits based on technologies 90–20 nm to develop recommendations for the design of energy-efficient devices. A technique for determining the key parameters of predictive MOSFET models in the subthreshold mode is considered. Expressions of the characteristics of inverter in the subthreshold region are obtained. Analysis shows a significant deterioration in the characteristics of CMOS elements in the subthreshold mode with a decrease in the dimensions of less than 90 nm. It is explained that when developing technology 90–20 nm, all measures were aimed at reducing leakage currents in the over threshold mode to reduce static power consumption. To improve the characteristics of CMOS elements in the subthreshold mode, it is necessary to optimize the design and technology to reduce the values of the subthreshold span, the DIBL coefficient and increase the characteristic current. The results may be useful for developers of energy-efficient equipment.

• NEURAL NETWORK METHOD OF PREDICTIVE CONTROL IN MICROGRIDS WITH MECHATRONIC WIND-GENERATOR SYSTEM

  N.К. Poluyanovich , N.I. Svetlichnyi , О. V. Kachelaev , М.N. Dubyago

  128-144

  2025-10-01

  Abstract ▼

  The influence of various factors on the accuracy of forecasting wind turbine generator (WTG) generation is considered. The optimal set of input parameters (day, month, time, wind speed, air temperature, atmospheric pressure and estimated power output of wind turbine) for forecasting is determined, and the methods of their processing are substantiated. The influence of influencing factors on the accuracy of forecasting the generated power of wind turbines was investigated. Profiles of input data for forecasting the power generation of wind power plants are constructed. The peculiarities of meteorological conditions for a year are considered, frequently occurring wind speed values are determined, etc., for the selection of an optimal wind turbine. It is shown that the meteorological conditions meet the passport requirements of the WTG selected for the region under consideration. Neural network (NN) models for forecasting the power generation of wind turbines are considered, the optimal NN is selected, the structure is built and the algorithm of NN for forecasting the generated power of wind turbines is developed. The developed mathematical model of wind power generation is aimed at improving accuracy and adaptability by taking into account key dynamic factors (wind speed and change in wind direction, air temperature and density, etc.). The combined wind turbine generation control method (MPPT + Pitch) is chosen to ensure a balance between efficiency and safety. The combined method of controlling the wind turbine generation (MPPT + Pitch) is chosen, which provides a balance between efficiency and safety. Based on the estimated generated power of wind turbines, and meteorological conditions at the location, the neural network model showed high accuracy in predicting the power of wind turbines. It is shown that the selected type of wind turbine combines technological reliability, cost-effectiveness and compliance with modern trends in wind energy. The NN model allows maintaining a balance between generated and consumed electricity, and, consequently, increases efficiency, reduces parasitic losses in the microgrid, and reduces wear and tear of equipment.

• MOBILE-CLOUD SYSTEM FOR SOLVING PHOTOGRAMMETRY TASKS IN INDUSTRY

  A.N. Samoylov, Y. M. Borodyansky

  2021-11-14

  Abstract ▼

  With the development of the capabilities of mobile devices and the increase in the availability
  of wireless communication, the possibilities of building industrial automation systems have
  significantly expanded. The quality of digital photography obtained with a smartphone camera
  makes it possible to build mobile systems based on computer vision: for example, photogrammetry
  systems. There are several factors to consider. The first factor is that the tasks of processing digital
  photography for industrial purposes remain resource-intensive and cannot be fully implemented
  only on the basis of a mobile device. Therefore, it is required to transfer the execution environment
  for resource-intensive tasks to third-party computing power available on demand. The second
  factor is the stability and bandwidth of the communication channel - mobile devices are usually
  needed in remote locations where the deployment of desktop computers is not possible. Therefore,
  using a smartphone only as a camera is not always justified, since the transfer of an unprocessed
  image may take a long time or even be impossible. The third factor hindering the widespread
  use of mobile devices in solving photogrammetric problems is the variability and constant
  emergence of new methods of image processing and analysis. It is necessary to centrally create
  and replenish libraries of such modules. Thus, the creation of mobile photogrammetric measuringsystems requires combining the computing power of cloud services and the mobility of smartphones. The article proposes a method for constructing photogrammetric measuring systems
  based on mobile cloud computing, which provides a dynamic balance of the computational load on
  the nodes of the system, as well as the variability of functionality on mobile devices of users

• DECISION-MAKING METHOD FOR TYPICAL PROCESSES MODELS FORMATION FOR CLOUD-BASED ENTERPRISE SYSTEMS

  А. А. Levchenko, V. V. Taratukhine , Y.A. Kravchenko

  2021-11-14

  Abstract ▼

  The article is devoted to solving the problem of creating a decision-making method in the formation
  of typical enterprise processes in information systems based on cloud technologies, also
  known as systems operating on the SaaS model (Software as a Service). The study's relevance is due
  to the novelty of cloud computing technology and the impossibility of applying the methods developed
  for on-Premise class systems. The study aims to improve the efficiency of using typical enterprise
  models in the implementation and use of SaaS systems. Increased efficiency affects the time and
  budget of the SaaS implementation project and operational costs after implementation. Achievement
  of the research goal is achieved by performing the following tasks: an analytical review of the research
  area for available methods, formalization and canonical formulation of the research task,
  description of the elements of project documentation as a single system of elements, and determination
  of relationships between them, development of a method for making decisions on the formation
  of models of typical processes, as structural elements of the system, verification of the method by
  determining the criterion for the effectiveness of the method and its comparison with the data of previous
  approaches. The research task is formalized as a canonical optimization problem with an objective
  function to maximize the efficiency criterion. The criterion of efficiency is given in the form of
  a formula that describes the degree of coverage of functional requirements to the target processes of
  the enterprise by standard models. The article describes the methods and algorithms used to solve
  similar problems, as well as their disadvantages and limitations. The proposed method is based for
  the first time on the theory of fuzzy sets and uses the Mamdani fuzzy inference algorithm to link a set
  of functional requirements and a set of system implementations. On the basis of the method, a software
  application was developed, and a computational experiment was carried out. The sample for
  testing the method and its comparison with existing analogs was formed on the basis of functional
  requirements for organizational processes of procurement management of large enterprises and the
  implementation of these requirements in SaaS systems on the SAP platform. The growth of the value
  of the efficiency criterion was confirmed in the case of the application of the proposed method, which
  demonstrates its advantage over the available alternative solutions already at the second iteration of
  use. As an example, a description of a typical process for creating a purchase requisition before and
  after applying the proposed method is presented.

• ANALYSIS OF ADVANCED COMPUTER TECHNOLOGIES FOR CALCULATION OF EXACT APPROXIMATIONS OF STATISTICS PROBABILITY DISTRIBUTIONS

  А.К. Melnikov, I.I. Levin, А.I. Dordopulo, L.M. Slasten

  2022-11-01

  Abstract ▼

  The paper is devoted to the evaluation of the hardware resource of computer systems for
  solving a computational-expensive problem such as calculation of the probability distributions of
  statistics by the second multiplicity method based on Δ-exact approximations for samples with a
  size of 320-1280 characters and an alphabet power of 128-256 characters, and with an accuracy
  of Δ=10-5. The total solution time should not exceed 30 days or 2.592·106 seconds for 24/7 computing.
  Owing to the use of the properties of the second multiplicity method, the computational complexity
  of the calculations can be brought to the range of 9.68·1022-1.60·1052 operations with the
  number of tested vectors of 6.50·1023-1.39·1050. The solution of this problem for the specified parameters
  of samples during the given time requires the hardware resource which cannot be provided
  by modern computer means such as processors, graphics accelerators, programmable logic
  integrated circuits. Therefore, in the paper we analyze the possibilities of promising quantum and
  photon technologies for solving the problem with the given parameters. The main advantage of
  quantum computer systems is the high speed of calculations for all possible parameter values.
  However, quantum acceleration will not be achieved to calculate the probability distributions of
  statistics due to the need to check all the obtained solutions. Here, the number of obtained solutions
  corresponds to the dimension of the problem. In addition, due to the current development
  level of the quantum hardware components, it is impossible to create and use the 120-qubit quantum
  computers for the solution of the considered problem. Photon computers can provide high
  computation speed at low power consumption and require the smallest number of nodes to solve
  the considered problem. However, unsolved problems with the physical implementation of efficient
  memory elements and the lack of available hardware components make the use of photon computer
  technologies impossible for calculation of the probability distributions of statistics in the near
  future (5-7 years). Therefore, it is most reasonable to use hybrid computer systems containing
  nodes of different architectures. To solve the problem on various hardware platforms (generalpurpose
  processors, GPUs, FPGAs) and configurations of hybrid computer systems, we suggest to
  use an architecture independent high-level programming language SET@L. The language combines
  the representation of calculations as sets and collections (based on the alternative set theory
  of P. Vopenka), the absolutely parallel form of the problem represented as an information graph,
  and the paradigm of aspect-oriented programming.

• A SYSTEM FOR AUTOMATING DOCUMENT FLOW AND MONITORING ECONOMIC SECURITY INCIDENTS BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES

  А.Е. Anpilogova , V.А. Anpilogov

  31-41

  2025-07-24

  Abstract ▼

  Automation of document flow is a key element of process optimization and efficiency improvement. Automation of document flow based on artificial intelligence improves the management of economic security incidents by optimizing work processes and reducing costs. The transition to automated document flow in Russia is associated with a complex regulatory framework and large-scale implementation costs at  enterprises. Automation helps to comply with legal requirements and reduces the risks of legal and financial consequences. Integration of digital signatures increases the efficiency of document approval.
  The implementation of automation systems supports national digital transformation goals. Automation of document flow reduces dependence on paper processes and facilitates the creation of centralized digital repositories. The implementation of document automation systems requires a strategic approach and careful planning. Document automation provides time savings, reduced errors and increased compliance with regulatory standards. The article discusses the theoretical foundations of BPM, integration of digital technologies and regulatory aspects specific to Russia. The proposed system combines monitoring with AI and IoT, provides real-time data processing, automates the creation of legal documents and reports. The workflow automation system is based on data integration, artificial intelligence technologies and seamless solutions. The system combines monitoring technologies, facial recognition and behavior analysis algorithms, a centralized database and a communication module. The system generates reports and legal documents certified by QES and ensures interaction with law enforcement agencies and security services. Implementation results: a 30–40% reduction in operating costs and a 50% reduction in losses. The system complies with digital transformation standards and supports the modernization of the national economy.

• MODEL AND ALGORITHM OF OPERATIONAL PLANNING OF LOGISTIC PROCESSES OF TIMELY DELIVERY OF CARGO WITH THE INTERACTION OF A GROUP OF ROBOTIC COMPLEXES

  Е.D. Grigoreva, V.А. Ushakov

  2025-04-27

  Abstract ▼

  The purpose of the study is to improve the quality of operational planning (program control) of logistics
  processes in the conditions of modern urban systems with the interaction of a group of robotic systems.
  The quality of management in this study will be assessed by the number of deliveries completed after
  established directive deadlines. The goal set during the study is decomposed into the following tasks: system
  analysis of the current state of research in the field of metropolitan logistics, implementation of a
  substantive and formal formulation of the problem of operational planning of logistics processes in a metropolis
  using a group of robotic complexes, development of a model and algorithm for operational planning
  of logistics processes in a metropolis using a grouping of robotic complexes, development of special
  model-algorithmic support and its software prototype for solving the problem of operational planning of
  logistics processes in a metropolis using a grouping of robotic complexes. Proactive (anticipatory) management
  of a group of robotic systems when solving transport and logistics problems in a metropolis within the framework of the “Smart City” concept allows increasing the economic efficiency of cargo delivery.
  The article examines the scientific and technical problem of synthesizing technologies (plans) for the timely
  delivery of small-sized cargo using a group of robotic systems. The scientific significance lies in the
  application of the concept of integrated (system) modeling and proactive (anticipatory) management, and
  the practical significance lies in ensuring timely delivery of goods using a group of robotic complexes in a
  metropolis. The article discusses an example of solving the problem of operational planning of logistics
  processes using the example of Innopolis using the characteristics of Yandex delivery robots (as robotic
  complexes). During the study, an analysis of various options for objective functions was carried out: maximizing
  profit and minimizing delivery time; profit maximization; minimizing time; minimizing the number
  of robotic systems. The following indicators were chosen to evaluate the results obtained: total profit from
  deliveries; the number of deliveries not delivered on time and the total number of completed orders.
  The most suitable objective functions for solving the problem are time minimization or simultaneous time
  minimization and profit maximization. In addition, the conclusion provides directions for further research