EVOLUTION OF THE OBSERVER STATE FROM PULSE TO PULSE
IN AN ELECTRIC DRIVE WITH A CONTACTLESS DC MOTOR
S.A. Vinokurov, O.A. Kiseleva, N.I. Rubtsov
The paper analyzes the current state in an electric drive with a contactless DC motor, considering that the control system in it is built as a hybrid, which is inherent in both discrete and continuous dynamics. The ideal vector control of a contactless DC motor can be described theoretically and used as a template for determining deviations in various control methods and evaluating their effectiveness. The paper compares the ideal control with discrete control, shows the possibility of implementing continuous control laws due to the displacement of control pulses in space and time. With pulse control, which is used in the electric drive at the present time, not only the pulse durations are calculated, but also the distances between them, that is, the beginning of the next pulse, and most importantly, the leading base vector is selected. The state observer in such a system performs a complex role, since there are delays in the system links, that must be considered, since they can disrupt the stability of the synchronous mode of the engine with the state observer. The paper presents a block diagram of a mathematical model of a state observer with a full-revolution detector.
Keywords: contactless DC motor, state observer, hybrid control, leading base vector.
FEATURES OF THE APPLICATION OF THE OBSERVER STATES
IN A CONTACTLESS DC MOTOR
O.A. Kiseleva, T.V. Popova, A.Y. Timoshkin
The paper deals with the analysis of the formation of discrete vector an equivalent tape to control brushless DC motor. The issues of using state observers instead of electromechanical rotor position sensors are considered. Shows the feature of constructing an observer status, for localdate that information on its input comes from continuous work-th current field, and the output it generates discrete torque control field switching of the windings of the synchronous motor power voltage inverter based on the motor parameters and actuators. To ensure synchronization, it is necessary to decide on the frequency of sensor polling and the possibility of processing this information, which leads to signal delays. It is necessary to take into account not only the time dependence associated with the beginning and end of the pulses, but also the spatial dependence associated with the alternation of the basic leading vectors. The estimation of control efficiency in electric drives with contactless DC motors and sensors of supervision is carried out. In some cases, the use of speed observers in the electric drive leads to a decrease in the speed control range. Graphs of transient processes in the electric drive at different values of the speed controller parameters are constructed.
Keywords: contactless DC motor, state observer, transient characteristics, discrete control field.
STRUCTURIZATION OF ENVIRONMENTAL INFORMATION WITH APPLICATION OF GEOINFORMATION TECHNOLOGIES
The article discusses the development of managerial decisions to improve the environment through the introduction of geographic information technologies, including methods for assessing and predicting the environmental situation based on monitoring approaches. The development of big data processing technologies has identified trends in the widespread implementation of real-time monitoring systems. In this regard, the task of monitoring natural objects is proposed to be solved as the task of determining and controlling the properties and states of a complex object in real time and actively interacting with the environment, as well as developing managerial decisions and recommendations. It is proposed to use the Fuzzy ART neural network as a mathematical apparatus for structuring environmental information, which has proven itself in real-time data processing. To visualize the received information and integrate the results of the network operation of the Fuzzy ART network into a geographic information system, it is proposed to use the Folium Python library, which is intended for graphical display of geographic data and contains all the necessary cartographic information. Using Folium, the results of the structuring of environmental data can be displayed directly on Google maps, which makes it possible to visually determine the boundaries of clusters and possible buffer zones when the map is scaled up.
Keywords: neural network, clustering, machine learning, adaptive resonance theory, Fuzzy ART network, GIS system.
EFFECTIVE METHOD OF DESIGNING CAD MODELS WITH LATTICE STRUCTURE
N.V. Tsipina, O.N. Chirkov, S.A. Slinchuk, I.V. Cheprasov, V.A. Madesov
This article shows how important it is to develop a convenient and simple method for designing lattice parts in production. The purpose of the entire experiment is to observe, analyze and solve problems in the design of lattice structures. The performance of modern tools of computer-aided design (CAD) systems was also evaluated. All the disadvantages and positive aspects of the developed method are indicated. The considered design method allows designers to choose the right lattice structure and its density. An essential part of this proposal is the use of equivalent lattice materials. This approach eliminates the need to design lattice-based CAD models and shortens the simulation time for FEMs. This methodology may be applicable in determining equivalent materials for other lattice structures. Equivalent materials also reduce FEM simulation time. The performance of modern tools of computer-aided design systems was evaluated to determine whether they adequately meet the requirements of additive manufacturing. The results show that modern CAD systems do not allow you to easily and quickly design lattice structures for additive manufacturing. It is necessary to develop modern CAE software to conduct finite element method analysis on a 3D lattice model.
Keywords: lattice structure, CAD software, finite element method (FEM).
ESTIMATION OF CAD CHARACTERISTICS IN THE CONTEXT OF DESIGNING MODELS WITH LATTICE STRUCTURE
N.V. Tsipina, O.N. Chirkov, S.A. Slinchuk, I.S. Bobylkin, E.I. Vorobiev
This article assesses the current characteristics of computer-aided design (CAD) systems in the context of the design of models with a lattice structure. During the design of the experiment, three variables were selected, two lattice structure templates, rods of lattice structures with two different sections and four sizes of parts were designed. The purpose of the whole experiment is to observe the problems that the user encounters when designing lattice structures in CAD software, as well as to determine the effect of the type and size of lattice structures on file sizes and whether modern file formats are suitable for the requirements of additive manufacturing. The obtained experimental results show that it is difficult to design CAD models with a lattice structure, since this process takes a lot of time and creates large files. In some cases, the program could not perform the desired operation. New requirements for the design of parts for additive manufacturing lead to new needs in computer-aided design. New research is needed to determine the most reliable and efficient methods for designing lattice structures in CAD software.
Keywords: CAD features, additive manufacturing, octet farm, cubic lattice structure.
MODIFICATION OF NEURAL NETWORK MODEL RKELM
WITH ADDITIONAL TRAINING
Y.A. Asanov, S.Y. Beletckaya
The aim of this work is developing of an artificial neural network model (ANN) capable of working in dynamically changing conditions. Despite a large number of research and development in this sphere, there are still no models that satisfy the limited resources of mobile systems (primarily – performance). This article proposes a developed modification of the Huang Extreme Learning Model, which differs from the original approach in the training process – training on common conditions, without increasing the weight matrix and the training sample, followed by further training for specific conditions. As a test sample of data, a dataset from the open source machine-learning repository UCI was used. Vast experiments were performed, the purpose of which was to identify the most suitable model, the choice was made from RKELM, SVM and ELM. The selection criteria for the model were performance and classification accuracy. The model with extreme training of Huang turned out to be the most suitable, it was used as the basis of the developed modification. The results of comparing the original and modified models are presented. The proposed approach surpassed the competition in speed and performance, while only slightly inferior in accuracy of data classification in the initial conditions, but turned out to be much more accurate in the new conditions in which the model was not trained.
Keywords: artificial neural network, RKELM modification, model with an additional training.
FORECASTING TIME SERIES USING EVENT BINDING
This article discusses the concept of modification of the time series analysis method, focused on integration with clustering methods in real-time training mode. Various methods of forecasting time series and machine learning are analyzed. The method described in the article predicts the behavior of the time series based on large data obtained from various sources and associated with existing transactions in the time series. This approach makes it possible to find the dependence of changes in certain indicators of the considered systems depending on various events. The performed research offers the concept of automated system training in real time with the possibility of further software implementation. The concept under consideration allows you to build forecasts for any time series, depending on various events, news and data that are in the public domain. An approach is proposed that links events to a transaction chart. The advantage of this approach is the ability to find various dependencies between events and various changes in indicators, for example: prices on exchanges, values of social indicators and many others.
Keywords: data analysis, forecasting, time series, big data, cluster analysis, data mining.
USING POTENTIALS IN LINEAR PROGRAMMING MODELS
I.Z. Mustaev, М.B. Guzairov, V.Y. Ivanov, N.К. Maksimova, Т.I. Mustaev
The article describes a linear optimization model, which is an interpretation of the linear programming model of Kantorovich L. V. The accumulated potentials are considered as variables, a brief description of which is given in the paper. Additionally, models of forecasted and full potentials are given. The use of accumulated potentials opens up possibilities for modeling objects with long life cycles. This significantly expands the scope of the linear programming methodology to study the behavior of socio-economic systems in market conditions. The foregoing is illustrated in relation to an enterprise of the engineering field. In particular, a comparison was made of the results obtained from the initial data and the results obtained by recalculating the potentials. Features of the dynamics of accumulated potentials allow us to solve the problem of using optimization approaches in conditions of the high volatility of the external environment, in the conditions of emerging markets. Efficiency models and models of time norms are described, which play an auxiliary role in the formation of a linear programming model. In addition, indicators of the potential time norm and potential intensity of the equipment used in this model are formalized. The final model for calculating the production program written using potentials is presented. The model reflects the optimal use of resources and takes the form of direct and dual linear programming problem reformulated with the use of accumulated potentials. The model includes a description of the potentials of the objective function and equations reflecting the potentials of resource constraints.
Keywords: linear programming, accumulated potential, forecasted potential, dynamic model, sociophysical object.
DEVELOPMENT OF A MATHEMATICAL MODEL OF THE PROCESS OF PROVIDING HIDDEN INFORMATION EXCHANGE IN RADIO SECURITY SYSTEMS AND A COMPUTATIONAL METHOD FOR ASSESSING THE STEALTH FOR THEM
To control large areas, radio security systems are currently being used that provide information collection from radio-distributed sensors distributed throughout the facility. When a person or a foreign object enters the sensor’s coverage area, the sensor detects the occurrence of an emergency and sends an alarm signal via radio channel to the system control panel. At the same time, it is known from the literature that radio security systems themselves are subject to destructive influences aimed at disrupting their performance. In this work, the author, based on the previously proposed mathematical model and generalization of the known literature, developed a mathematical model of the process of providing hidden information exchange in radio security systems, taking into account the destabilizing effects (for example, imposing false data or suppressing interference) on the transmitted signals in the communication channel. A computational method has also been developed for assessing the stealth of information exchange in radio security systems based on fuzzy logic, the use of which under conditions of poorly structured and difficult formalizability of the source data and also in the conditions of a complex of destructive influences, can potentially help to more adequately assess the stealth of radio security systems. The results can be used to study the stealth of known and promising radio security systems. It is also possible to use the results obtained to increase the stealth of known and promising radio security systems.
Keywords: mathematical model, computational method, stealth, radio channel, radio security systems.
ARCHITECTURE OF A CLOUD SYSTEM FOR DISTRIBUTING MULTIMEDIA CONTENT IN CYBER-PHYSICAL SYSTEMS
Keywords: multimedia, human-machine interaction, distributed systems, content delivery systems, cyber-physical systems, data bus.