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The using of determining the measure of interaction between channels when choosing the configuration structure of a control system for complex dynamic objects is considered in the work. The main methods for determining the measure of interaction between subsystems of complex control systems based on the methods RGA (Relative Gain Array), Dynamic RGA, HIIA (Hankel Interaction Index Array), PM (Participation matrix) are presented. When choosing a control configuration, simple configurations are preferable, as they are simple in design, maintenance and more resistant to failures. However, complex configurations provide higher performance control systems. Processes in large dynamic objects are characterized by a high degree of interaction between process variables. For the design of the control structure interaction measures are used, namely, the selection of the control structure and the decision on the configuration of the controller. The choice of control structure is to determine which dynamic connections should be used to design the controller. When a structure is selected, connections can be used to configure the controller. For large systems, it is proposed to pre-group the components of the vectors of input and output signals of the actuators and sensitive elements into sets in which the number of variables decreases significantly in order to select a control structure. A quantitative estimation of the decentralization of the control system based on minimizing the sum of the off-diagonal elements of the PM matrix is given. An example of estimation the measure of interaction between components of strong coupled subsystems and the measure of interaction between components of weak coupled subsystems is given. A quantitative estimation is given of neglecting the interaction of components of weak coupled subsystems. The construction of a weighted graph for visualizing the interaction of the subsystems of a complex system is considered. A method for the formation of the controllability gramian on the vector of output signals that is invariant to state vector transformations is proposed in the paper. An example of the decomposition of the stabilization system of the components of the flying vehicle angular velocity vector is given. The estimation of measures of the mutual influence of processes in the channels of control systems makes it possible to increase the reliability of the systems when accounting for the use of analytical redundancy of information from various devices, which reduces the mass and energy consumption. Methods for assessing measures of the interaction of processes in subsystems of control systems can be used in the design of complex systems, for example, motion control systems, orientation and stabilization systems of vehicles.

The article presents the results of numerical modeling of the vortex spatial non-stationary motion of the medium arising near the lateral and bottom surfaces of the descent module during its movement in the atmosphere of Mars. The numerical study was performed for the high-speed streamline regime at various angles of attack. Mathematical modeling was carried out on the basis of the Navier – Stokes model and the model of equilibrium chemical reactions for the Martian atmosphere gas. The simulation results showed that under the considered conditions of the descent module motion, a non-stationary flow with a pronounced vortex character is realized near its lateral and bottom surfaces. Numerical calculations indicate that, depending on the angle of attack, the nonstationarity and vortex nature of the flow can manifest itself both on the entire lateral and bottom surfaces of the module, and, partially, on their leeward side. For various angles of attack, pictures of the vortex structure of the flow near the surface of the descent vehicle and in its near wake are presented, as well as pictures of the gas-dynamic parameters fields. The non-stationary nature of the flow is confirmed by the presented time dependences of the gas-dynamic parameters of the flow at various points on the module surface. The carried out parametric calculations made it possible to determine the dependence of the aerodynamic characteristics of the descent module on the angle of attack. Mathematical modeling is carried out on the basis of the conservative numerical method of fluxes, which is a finitevolume method based on a finite-difference writing of the conservation laws of additive characteristics of the medium using «upwind» approximations of stream variables. To simulate the complex vortex structure of the flow over descent module, the nonuniform computational grids are used, including up to 30 million finite volumes with exponential thickening to the surface, which made it possible to reveal small-scale vortex formations. Numerical investigations were carried out on the basis of the developed software package based on parallel algorithms of the used numerical method and implemented on modern multiprocessor computer systems. The results of numerical simulation presented in the article were obtained using up to two thousand computing cores of a multiprocessor complex.

Sensor fusion is one of the important solutions for the perception problem in self-driving cars, where the main aim is to enhance the perception of the system without losing real-time performance. Therefore, it is a trade-off problem and its often observed that most models that have a high environment perception cannot perform in a real-time manner. Our article is concerned with camera and Lidar data fusion for better environment perception in self-driving cars, considering 3 main classes which are cars, cyclists and pedestrians. We fuse output from the 3D detector model that takes its input from Lidar as well as the output from the 2D detector that take its input from the camera, to give better perception output than any of them separately, ensuring that it is able to work in real-time. We addressed our problem using a 3D detector model (Complex-Yolov3) and a 2D detector model (Yolo-v3), wherein we applied the image-based fusion method that could make a fusion between Lidar and camera information with a fast and efficient late fusion technique that is discussed in detail in this article. We used the mean average precision (mAP) metric in order to evaluate our object detection model and to compare the proposed approach with them as well. At the end, we showed the results on the KITTI dataset as well as our real hardware setup, which consists of Lidar velodyne 16 and Leopard USB cameras. We used Python to develop our algorithm and then validated it on the KITTI dataset. We used ros2 along with C++ to verify the algorithm on our dataset obtained from our hardware configurations which proved that our proposed approach could give good results and work efficiently in practical situations in a real-time manner.

The paper considers the possibility of comparing and classifying dynamical systems based on topological data analysis. Determining the measures of interaction between the channels of dynamic systems based on the HIIA (Hankel Interaction Index Array) and PM (Participation Matrix) methods allows you to build HIIA and PM graphs and their adjacency matrices. For any linear dynamic system, an approximating directed graph can be constructed, the vertices of which correspond to the components of the state vector of the dynamic system, and the arcs correspond to the measures of mutual influence of the components of the state vector. Building a measure of distance (proximity) between graphs of different dynamic systems is important, for example, for identifying normal operation or failures of a dynamic system or a control system. To compare and classify dynamic systems, weighted directed graphs corresponding to dynamic systems are preliminarily formed with edge weights corresponding to the measures of interaction between the channels of the dynamic system. Based on the HIIA and PM methods, matrices of measures of interaction between the channels of dynamic systems are determined. The paper gives examples of the formation of weighted directed graphs for various dynamic systems and estimation of the distance between these systems based on topological data analysis. An example of the formation of a weighted directed graph for a dynamic system corresponding to the control system for the components of the angular velocity vector of an aircraft, which is considered as a rigid body with principal moments of inertia, is given. The method of topological data analysis used in this work to estimate the distance between the structures of dynamic systems is based on the formation of persistent barcodes and persistent landscape functions. Methods for comparing dynamic systems based on topological data analysis can be used in the classification of dynamic systems and control systems. The use of traditional algebraic topology for the analysis of objects does not allow obtaining a sufficient amount of information due to a decrease in the data dimension (due to the loss of geometric information). Methods of topological data analysis provide a balance between reducing the data dimension and characterizing the internal structure of an object. In this paper, topological data analysis methods are used, based on the use of Vietoris-Rips and Dowker filtering to assign a geometric dimension to each topological feature. Persistent landscape functions are used to map the persistent diagrams of the method of topological data analysis into the Hilbert space and then quantify the comparison of dynamic systems. Based on the construction of persistent landscape functions, we propose a comparison of graphs of dynamical systems and finding distances between dynamical systems. For this purpose, weighted directed graphs corresponding to dynamical systems are preliminarily formed. Examples of finding the distance between objects (dynamic systems) are given.

The numerical solving of the system of high-temperature radiative gas dynamics (HTRGD) equations is a computationally laborious task, since the interaction of radiation with matter is nonlinear and non-local. The radiation absorption coefficients depend on temperature, and the temperature field is determined by both gas-dynamic processes and radiation transport. The method of splitting into physical processes is usually used to solve the HTRGD system, one of the blocks consists of a joint solving of the radiative transport equation and the energy balance equation of matter under known pressure and temperature fields. Usually difference schemes with orders of convergence no higher than the second are used to solve this block. Due to computer memory limitations it is necessary to use not too detailed grids to solve complex technical problems. This increases the requirements for the order of approximation of difference schemes. In this work, bicompact schemes of a high order of approximation for the algorithm for the joint solution of the radiative transport equation and the energy balance equation are implemented for the first time. The proposed method can be applied to solve a wide range of practical problems, as it has high accuracy and it is suitable for solving problems with coefficient discontinuities. The non-linearity of the problem and the use of an implicit scheme lead to an iterative process that may slowly converge. In this paper, we use a multiplicative HOLO algorithm named the quasi-diffusion method by V.Ya.Goldin. The key idea of HOLO algorithms is the joint solving of high order (HO) and low order (LO) equations. The high-order equation (HO) is the radiative transport equation solved in the energy multigroup approximation, the system of quasi-diffusion equations in the multigroup approximation (LO₁) is obtained by averaging HO equations over the angular variable. The next step is averaging over energy, resulting in an effective one-group system of quasi-diffusion equations (LO₂), which is solved jointly with the energy equation. The solutions obtained at each stage of the HOLO algorithm are closely related that ultimately leads to an acceleration of the convergence of the iterative process. Difference schemes constructed by the method of lines within one cell are proposed for each of the stages of the HOLO algorithm. The schemes have the fourth order of approximation in space and the third order of approximation in time. Schemes for the transport equation were developed by B.V. Rogov and his colleagues, the schemes for the LO₁ and LO₂ equations were developed by the authors. An analytical test is constructed to demonstrate the declared orders of convergence. Various options for setting boundary conditions are considered and their influence on the order of convergence in time and space is studied.

The features of the component circuits method (MCC) in modeling chemical-technological systems (CTS) are considered, taking into account its practical significance. The software and algorithmic implementation of which is currently a set of computer modeling programs MARS (Modeling and Automatic Research of Systems). MARS allows the development and analysis of mathematical models with specified experimental parameters. Research and calculations were carried out using a specialized software and hardware complex MARS, which allows the development of mathematical models with specified experimental parameters. In the course of this work, the model of a perfect-mixing reactor was developed in the MARS modeling environment taking into account the physicochemical features of the uranium extraction process in the presence of nitric acid and tributyl phosphate. As results, the curves of changes of the concentration of uranium extracted into the organic phase are presented. The possibility of using MCC for the description and analysis of CTS, including extraction processes, has been confirmed. The use of the obtained results is planned to be used in the development of a virtual laboratory, which will include the main apparatus of the chemical industry, as well as complex technical controlled systems (CTСS) based on them and will allow one to acquire a wide range of professional competencies in working with “digital twins” of real control objects, including gaining initial experience working with the main equipment of the nuclear industry. In addition to the direct applied benefits, it is also assumed that the successful implementation of the domestic complex of computer modeling programs and technologies based on the obtained results will make it possible to find solutions to the problems of organizing national technological sovereignty and import substitution.

Computer-aided assembly planning of complex products is an important area of modern information technology. The sequence of assembly and decomposition of the product into assembly units largely depend on the mechanical structure of a technical system (machine, mechanical device, etc.). In most modern research, the mechanical structure of products is modeled using a graph of connections and its various modifications. The coordination of parts during assembly can be achieved by implementing several connections at the same time. This generates a $k$-ary basing relation on a set of product parts, which cannot be correctly described by graph means. A hypergraph model of the mechanical structure of a product is proposed. Modern discrete manufacturing uses sequential coherent assembly operations. The mathematical description of such operations is the normal contraction of edges of the hypergraph model. The sequence of contractions that transform the hypergraph into a point is a description of the assembly plan. Hypergraphs for which such a transformation exists are called $s$-hypergraphs. $S$-hypergraphs are correct mathematical models of the mechanical structures of any assembled products. A theorem on necessary conditions for the contractibility of $s$-hypergraphs is given. It is shown that the necessary conditions are not sufficient. An example of a noncontractible hypergraph for which the necessary conditions are satisfied is given. This means that the design of a complex technical system may contain hidden structural errors that make assembly of the product impossible. Therefore, finding sufficient conditions for contractibility is an important task. Two theorems on sufficient conditions for contractibility are proved. They provide a theoretical basis for developing an efficient computational procedure for finding all $s$-subgraphs of an $s$-hypergraph. An $s$-subgraph is a model of any part of a product that can be assembled independently. These are, first of all, assembly units of various levels of hierarchy. The set of all $s$-subgraphs of an $s$-hypergraph, ordered by inclusion, is a lattice. This model can be used to synthesize all possible sequences of assembly and disassembly of a product and its components. The lattice model of the product allows you to analyze geometric obstacles during assembly using algebraic means.

Scheduling computational workflows represented by directed acyclic graphs (DAGs) is crucial in many areas of computer science, such as cloud/edge tasks with distributed workloads and data mining. The complexity of online DAG scheduling is compounded by the large number of computational nodes, data transfer delays, heterogeneity (by type and processing power) of executors, precedence constraints imposed by DAG, and the nonuniform arrival of tasks. This paper introduces the Multi-Agent Local Voting Protocol (MLVP), a novel approach focused on dynamic load balancing for DAG scheduling in heterogeneous computing environments, where executors are represented as agents. The MLVP employs a local voting protocol to achieve effective load distribution by formulating the problem as a differentiated consensus achievement. The algorithm calculates an aggregated DAG metric for each executor-node pair based on node dependencies, node availability, and executor performance. The balance of these metrics as a weighted sum is optimized using a genetic algorithm to assign tasks probabilistically, achieving efficient workload distribution via information sharing and reaching consensus among the executors across the system and thus improving makespan. The effectiveness of the MLVP is demonstrated through comparisons with the state-of-the-art DAG scheduling algorithm and popular heuristics such as DONF, FIFO, Min- Min, and Max-Min. Numerical simulations show that MLVP achieves makepsan improvements of up to 70% on specific graph topologies and an average makespan reduction of 23.99% over DONF (state-of-the-art DAG scheduling heuristic) across randomly generated diverse set of DAGs. Notably, the algorithm’s scalability is evidenced by enhanced performance with increasing numbers of executors and graph nodes.

We investigate machine learning methods with a certain kind of decision rule. In particular, inverse-distance method of interpolation, method of interpolation by radial basis functions, the method of multidimensional interpolation and approximation, based on the theory of random functions, the last method of interpolation is kriging. This paper shows a method of rapid retraining “model” when adding new data to the existing ones. The term “model” means interpolating or approximating function constructed from the training data. This approach reduces the computational complexity of constructing an updated “model” from $O(n^3)$ to $O(n^2)$. We also investigate the possibility of a rapid assessment of generalizing opportunities “model” on the training set using the method of cross-validation leave-one-out cross-validation, eliminating the major drawback of this approach — the necessity to build a new “model” for each element which is removed from the training set.

This article explores a method of machine learning based on the theory of random functions. One of the main problems of this method is that decision rule of a model becomes more complicated as the number of training dataset examples increases. The decision rule of the model is the most probable realization of a random function and it's represented as a polynomial with the number of terms equal to the number of training examples. In this article we will show the quick way of the number of training dataset examples reduction and, accordingly, the complexity of the decision rule. Reducing the number of examples of training dataset is due to the search and removal of weak elements that have little effect on the final form of the decision function, and noise sampling elements. For each $(x_i,y_i)$-th element sample was introduced the concept of value, which is expressed by the deviation of the estimated value of the decision function of the model at the point $x_i$, built without the $i$-th element, from the true value $y_i$. Also we show the possibility of indirect using weak elements in the process of training model without increasing the number of terms in the decision function. At the experimental part of the article, we show how changed amount of data affects to the ability of the method of generalizing in the classification task.