APPLICATION OF ANN IN HUMAN-MACHINE INTERFACES
The article continues the cycle of the author’s works on the subject of HIL-simulation. The article proposes an algorithm for the decomposition of any radio system and the subsequent coupling of its parts by adjusting only one of the two stabilizing parameters of the coupling scheme. In addition, the possibility of using a coupling scheme as a matching device between fragments of the system through the aspect of system stability was analyzed. All this makes it possible to significantly reduce the amount of debugging work performed in HIL-simulation of radio systems, both in the field of research of elementary systems and in working out options for creating complex multisystems. As a proof of the correctness of the proposed method, an analytical calculation was performed, in general, showing the possibility of adjusting only one stabilizing parameter in the coupling scheme of a decomposed system, while convergence of the parameters of the divided system to the parameters of the original system can be achieved in several iterations. In some cases, this convergence can be achieved in one iteration. In the conclusion of the article, the calculation was performed using a numerical example for practical confirmation of the proposed method. For clarity and correct understanding of the described actions, illustrations are given of both the operations performed and the results of the calculations..
Keywords: :stabilizing parameter, system decomposition, coupling scheme, HIL-modeling, radio system, Cramer’s rule, Schur complement.
MULTIOBJECTIVE OPTIMIZATION OF BAND-PASS FILTERS CHARACTERISTICS USING HEURISTIC ALGORITHM
The problem of multiobjective optimization of band pass filter (BPF) is investigated. There were three objectives considered: a nonuniformity of attenuation in the pass band, a minimum attenuation in the stop band and a nonuniformity of delay time in the pass band. The first method of solution was to derive Pareto-optimal approximations for BPF from such for low pass filter (LPF) by means of reactance frequency transform. The second method was to search optimal approximation for BPF directly. In the both methods the heuristic algorithm was applied. This algorithm searches out the set of Pareto optimal solutions and uses multistart for searching of global extreme for each point of Pareto front. The numerical experiments showed that for cases with wide pass band of BPF and comparatively poor-quality indexes of gain frequency response the second method can give lower nonuniformity of delay time than the first one when other objectives are the same. This result means that Pareto-optimality does not persist in the frequency transform in such cases. At once in the cases with narrow pass band of BPF or comparatively good quality indexes of gain frequency response the direct search provides no preferences.
Keywords: :transfer function, band pass filter, approximation, Pareto optimality, heuristic algorithm.
INTELLIGENT CONTROL OF MULTISTAGE SYSTEMS OF METALLURGICAL PRODUCTION
To date, the level of development of metallurgical production imposes high requirements to production management systems and the quality of steel products, due to the development of information technology. Metallurgical production from the point of view of management and multistage character of production is a complex, large system with different characteristics of subsystems and elements of processing. Traditional methods of modeling for the management of such systems are ineffective, as one of the main problems is the choice of optimal management decisions taking into account current situations and restrictions on changes in the values of technological parameters. In this regard, there is a need to develop a methodology that would improve the management of technological systems, organize decision-making support in the face of uncertainty, to ensure the speed and accuracy of information to improve the quality of metal products and technical and economic indicators and the reliability of production. The application of new methods of analysis of complex production systems of information processing, management improvement and decision-making will improve the efficiency of enterprises and reduce the proportion of low-quality products. The aim of the study is to use new methods of analysis of complex production systems of information processing, improvement of management and decision-making, which will improve the efficiency of enterprises and reduce the share of low-quality products. As a result, the formalization of the problem of integrated management of output indicators of product quality, taking into account the uncertainty of internal factors of metallurgical production. The software implementation of the algorithms will increase the efficiency of decision-making by determining the optimal technological parameters from the range of permissible values.
Keywords: :metallurgical production, intelligent control support, multi-stage technology in the context of uncertainty.
APPLICATION OF ANN IN HUMAN-MACHINE INTERFACES
UDC 004.5, 612.817.2
N.A.Budko, R.Y.Budko, A.Y.Budko
Currently, there are almost no areas of human activity that are not concerned with automation, which has received the greatest popularity over the past few years. To date, the methods that are based on the organization and functioning of biological neural networks have become most famous. The article provides an analytical review of the possibilities of using artificial neural networks (ANN) in the development of human-machine interfaces based on various physical principles of interaction with the human body. This interface provides user interaction with the machines it manages. Examples of the use of human-machine interfaces in household, medical and military areas are given. Efficiency is due to the flexibility, nonlinearity, speed and learning of systems based on neural networks. Thus, users can monitor the process with great precision, achieving the best result. The problems of using ANNs in control systems of technical objects based on the recognition of natural speech, tracking the direction of sight, analysis of the electrical activity of the brain and muscle fibers of a person are considered. The tasks of pre-processing information, classification, analysis of the result obtained by processing the neural network are described.
Keywords: :man-machine interface, artificial neural networks, control, electromyogram, electroencephalogram.
OPTIMAL DESING OF THE EXPERIMENT WITH THE ACTIVE IDENTIFICATION OF FUZZY LINEAR REGRESSION MODELS
The problem of constructing linear regression models with respect to parameters and factors for the case of sufficiently wide ranges of variable variation is considered. It is proposed to use fuzzy linear regression models to restore the dependencies. The problem of a priori optimal experiment planning for fuzzy linear regression model’s identification is considered. At the same time, the area of determining the acting factors is divided into 2-3 fuzzy partitions. This model representation provides the restoration of dependencies which differ in different parts of the region determination of the input variables. The problem of construction and optimal planning of the experiment is formulated. A numerical algorithm in the form of gradient descent is used to construct optimal plans. The effectiveness of the obtained solutions is controlled by the implementation of the necessary and sufficient conditions of optimality. The problem of constructing an optimal plan is considered for the case of one and two factors with the number of fuzzy partitions 2 and 3. The analysis of the characteristics of optimal plans depending on the width of the intersection zone of fuzzy partitions is carried out. It is noted that with a decrease in the zone of intersection of fuzzy partitions, the efficiency of optimal plans increases, which affects the reduction of the determinants of dispersion matrices and their trace. Other characteristic features of the synthesized-optimal plans are noted. The conclusion is made about the efficiency of active identification of fuzzy linear regression models.
Keywords: :fuzzy regression, membership function, optimal design of experiment, the criterion of optimality.
FORECESSION ELECTROMYOGRAPHY RECOGNITION AND GESTURES SELECTION FOR PROTESIS CONTROL
UDC 612.743, 612.817.2
R.Y. Budko, N.N. Chernov, N.A. Budko, A.Y. Budko
The relevance of this study is due to one of the main problems existing today in the field of building man-machine interfaces – is the creation of an effective management system that interacts directly with the user and external devices replacing functions (prostheses, wheelchairs, etc.). In this regard, this work is devoted to the study of the possibility of using physiological gestures from the daily life of a person to control the prosthesis with the safety of the forearm for at least one third. The leading approach to the study of this problem is the use of methods of statistical processing of experimental data, digital signal processing, machine learning algorithms and pattern recognition. This approach allows a comprehensive study of the electromyogram (EMG) of the forearm when making voluntary movements at different levels of the implementation of the myo-control system. The article presents the results of the EMG study recorded for 11 arbitrary movements from a group of subjects, describes the procedure for pre-processing the EMG and identifying characteristic features for signal recognition, discloses a method for classifying movements using an artificial neural network based on radial basic functions (RBF). Eight of the most suitable for classification movements were identified and ranked according to the classification accuracy: relaxation (like zero movement), hand opening, fist, hand flexion, hand supination, hand extension, hand pronation, pinch. The materials of the article are of practical value for building systems based on the human-machine interface, as well as for classification tasks in electrophysiology applications.
Keywords: :electromyogram, prosthesis, biocontrol, human-machine interface, machine learning, artificial neural networks.
SOFTWARE IMPLEMENTATION INTELLIGENT SYSTEMS DECISION-MAKING WHEN MANAGING NUCLEAR ENERGY FACILITIES
UDC 004: 681.5
V. P. Povarov
The work is devoted to the development of the software complex of the intellectual decision-making system in the problems of management of the processes of functioning of nuclear power facilities. It is shown that the construction of the software complex requires the choice of structure based on the analysis of the tasks assigned to the software. Taking into account the developed mathematical software, implemented in the form of a set of mathematical models that allow to analyze data by processing the input information, and algorithms that perform the formation of the system structure, its optimization and ensure its operation, the following main functions were identified and implemented: the formation of a regression model depending on the input information flow of informative data; the formation of a neural network structure depending on the input information flow of data; configuration of system parameters in order to ensure the required quality of its functioning; visual display of information about the quality of the software; providing data storage in an accessible and easy to understand form; providing storage of configurable system parameters and their dynamics in the learning process ANFIS-like neural network model. The proposed engineering solutions have improved the quality of decision-making due to the efficiency and reliability of the processed information, as well as by reducing the overall error of the forecast.
Keywords: :decision-making system, multiparameter monitoring, forecasting, database, knowledge base, fuzzy neural network.
NUMERICAL MODELING OF DIFFUSION OF CONTAMINANTS IN RIVERS WITH REGARD OF DIFFUSE TERM
UDC 004.94: 004.9.032.26
V.Y. Vishnevetskiy, I.B. Starchenko
This paper deals with the problems of modeling and forecasting the spread of pollutants in the water flow in the river. The state reports of the Ministry of natural resources and ecology are analyzed, on the basis of which the importance of tracking the discharge of pollutants into the rivers, which are carriers of pollutants from the water flow rate, was shown. Of particular importance is the importance of predicting the spread of the concentration of pollutants in the river bed and the further discharge of water into water bodies. In this article we consider two-dimensional modeling of the process of diffusion of pollutants in rivers, taking into account the diffuse factor. The symmetric parabolic equation of the second order was used as the basic one. Numerical modeling of the equations for different flow rates of water in the river and the velocity of the diffusion process was done in Matlab software. Three-dimensional profiles of concentration distribution depending on the river flow rate in the range of 0.1-1 m/s and the pollutant diffusion rate in the range of 0.5-10 m/s are plotted. It is shown that at low diffusion rates the concentration is almost constant, and the high diffusion rate gives a sharp increase in the concentration at the initial time, followed by a smooth decline.
Keywords: : river flow, concentration, pollutants, numerical solution of equations, diffuse term, water resources monitoring, convection-diffusion equation.
FUZZY MODELS OF THE ESTIMATION OF THE LEVEL OF ERGONOMICS OF TECHNICAL SYSTEMS AND ITS EFFECTS ON THE STATE OF HEALTH OF A HUMAN OPERATOR TAKING INTO ACCOUNT THE FUNCTIONAL RESERVE OF THE BODY
N.A.Korenevskiy, S.N.Rodionova, T.N.Govorukhina, M.A.Myasoedova
The paper studies the impact of the ergonomics of technical systems on the emergence and development of occupational diseases of a human operator, taking into account the functional reserve of his body. In view of the complexity of the analytical description of the interaction mechanisms of the human-technical system, a methodology for the synthesis of hybrid fuzzy decision rules, focused on solving poorly formalizable problems, was chosen as the mathematical apparatus of research. In the framework of the chosen methodology, the individual estimates of the ergonomic level by basic indicators are averaged by the functions of the ergonomic level, which are aggregated into final decision rules. Evaluation of the impact of ergonomic level and other significant risk factors is carried out using the appropriate membership functions, which are aggregated into fuzzy models of forecasting and early diagnosis of occupational diseases. Using the example of diseases of the nervous system in drivers of Russian-made tractors, it has been shown that the simultaneous consideration of ergonomic risk factors and the size of the functional reserve with other significant endogenous and exogenous factors helps to improve the quality of decisions made about the health status of the human body. At the same time, confidence in the correctness of the prognosis and early diagnosis exceeds 0.86, which allows us to recommend the resulting decision-making models in the practice of occupational physicians.
Keywords: : ergonomics, functional reserve, health status, membership functions, fuzzy logic, prediction, early diagnosis.