Performance Assessment Of Operators Under Digital Simulator-Based Training In Automated Industrial Systems,
2025
Tashkent state technical university named after Islam Karimov, Tashkent, Uzbekistan. Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +998-99-852-66-65.
Performance Assessment Of Operators Under Digital Simulator-Based Training In Automated Industrial Systems, Kamola Abdullaeva
Chemical Technology, Control and Management
This article proposes a comprehensive approach to training process operators, based on computer simulators integrated with digital twins, SCADA/DCS systems, real production data, and artificial intelligence algorithms. This approach is particularly relevant given the increased requirements for safety, productivity, and reliability of industrial facilities, as human factors are often the main cause of accidents (up to 60-80% of cases). The architecture of the simulator complex is designed to accurately emulate steady-state, transient, and pre-emergency operating modes of equipment, which are not achievable under actual production conditions. The experiment compared the training effectiveness of two groups of operators: one that used …
Expansion Of The Functionality Of Discrete Fiber-Optic Liquid Level Sensors,
2025
Tashkent State Technical University. Address: st. Universitetskaya 2, 100095, Tashkent, Republic of Uzbekistan. E-mail: [email protected];
Expansion Of The Functionality Of Discrete Fiber-Optic Liquid Level Sensors, Azimjon Mamadaliyevich Khusanov, Yuriy Gennadyevich Shipulin
Chemical Technology, Control and Management
The article examines the problems and prospects of creating discrete fiber-optic liquid level gauges. Functional diagrams of single-channel and multi-channel discrete fiber-optic liquid level meters are presented. Examining the challenges of keeping this system running continuously reveals that sustaining its required reliability necessitates replacing malfunctioning measurement systems with operational ones. Investigations into differential equation models demonstrate that system recovery and failure events occur independently and follow a Poisson distribution pattern.
Investigation Of Nonlinear Magnetic Circuits Of Measuring Transducers With A Special Parameter Distribution Structure,
2025
Tashkent State Transport University. Address: 1 Temiryolchilar Street, Mirobod District, Tashkent, Republic of Uzbekistan. E-mail: javhar2019mail.ru.
Investigation Of Nonlinear Magnetic Circuits Of Measuring Transducers With A Special Parameter Distribution Structure, Javhar Sulton O'G'Li Fayzullayev
Chemical Technology, Control and Management
The article proposes a new analytical method for investigating nonlinear magnetic circuits with a special structure of parameter distribution. The method is based on introducing into the system of nonlinear differential equations of such circuits the condition that the second derivative of the magnetic flux along the length of the circuit is equal to zero, as well as on the assumption that one of the geometric parameters of the studied magnetic circuit – the size of the air gap between the ferromagnetic rods, their thickness, width, or the linear value of the number of turns of the distributed excitation winding …
Empirical Analysis Of Machine Learning Models For Predicting Equipment Failures Using Iot Sensor Data,
2025
Tashkent State Technical University, Address: 100095, Tashkent city, st. University 2, Republic of Uzbekistan. E-mail: [email protected].
Empirical Analysis Of Machine Learning Models For Predicting Equipment Failures Using Iot Sensor Data, Yusuf Shodiyevich Avazov
Chemical Technology, Control and Management
This article examines the problem of detecting and predicting industrial equipment faults using IoT sensor data through machine learning techniques. Sensor readings such as temperature, vibration, pressure, voltage, and current, as well as FFT-based features, were statistically analyzed. Class imbalance and low signal informativeness were identified as key factors limiting model accuracy. Results obtained from Logistic Regression, Random Forest, and XGBoost models were comparatively evaluated, showing that when ROC-AUC values remain around 0.5, distinguishing fault and non-fault states becomes challenging. Correlation and feature-importance analyses confirmed the absence of strong dominant indicators. The findings highlight the need to improve sensor architecture …
Current Trends In Industrial Gas Furnace Control And Monitoring Systems,
2025
Tashkent State Technical University, Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected].
Current Trends In Industrial Gas Furnace Control And Monitoring Systems, Utkir Uktam O'Gli Kholmanov
Chemical Technology, Control and Management
This paper presents a critical review of modern control methods applied to industrial gas-fired furnaces. Conventional PID controllers and their advanced modifications, including Advanced Process Control (APC) and cascade control schemes, are analyzed alongside Model Predictive Control (MPC) approaches. In addition, intelligent control algorithms—such as fuzzy logic and neuro-fuzzy systems (Fuzzy, ANFIS)—are examined. The study also considers advanced sensing technologies, including Tunable Diode Laser Absorption Spectroscopy (TDLAS), acoustic pyrometry, and infrared pyrometers, as well as digital twins and CFD-based modeling techniques. Particular attention is given to a comparative evaluation of control strategies based on key performance criteria, including energy efficiency, …
Skeleton-Based Human Action Recognition Using Spatio-Temporal Latent Features With A Gcn Model,
2025
Tashkent State Technical University. Address: 2 Universitetskaya st., 100095, Tashkent, Uzbekistan. E-mail: [email protected];
Skeleton-Based Human Action Recognition Using Spatio-Temporal Latent Features With A Gcn Model, Avazjon Marakhimov, Kabul Khudaybergenov, Mominov Zakhriddin
Chemical Technology, Control and Management
Owing to its resilience to visual noise and viewpoint variations, skeleton-based analysis has become a cornerstone of human action recognition research. Despite its practical significance, existing methodologies often suffer from a reliance on single-stream skeletal representations, which fail to encompass the full complexity of action features. This study introduces Latent Features for Human Action Recognition (LFHAR), a novel architecture designed to overcome these limitations by utilizing diverse spatio-temporal latent representations for improved feature extraction. The approach applies graph-based transformations to individual skeletal frames in temporal sequences, then arranges the derived graph features into spatio-temporal matrices. Evaluation of standard datasets demonstrates …
Analysis Of A Cloud-Based Robot Motion Planning System,
2025
Azerbaijan State Oil and Industry University. Address: Azadliq Avenue 34, AZ1010, Baku, Azerbaijan. E-mail: [email protected].
Analysis Of A Cloud-Based Robot Motion Planning System, Yusif Mardanzade, Latafat Abbas Gardashova
Chemical Technology, Control and Management
As a result of the integration of cloud computing technologies into the field of robotics, the concept of "cloud robotics" has emerged. Unlike traditional robots, cloud-based robot systems remove computation, memory, and even some software from the local device and rely on remote resources obtained over the network. This approach ensures that robots are not limited only by their internal computing capabilities and allows them to take advantage of the wide range of opportunities offered by the cloud infrastructure. As a result, robots have access to large databases, highly parallel computing, and collective learning capabilities anytime and anywhere. In addition, …
Intelligent Decision-Making Systems In Smart Greenhouses,
2025
Tashkent State Technical University named after Islam Karimov, 100095, Tashkent, Uzbekistan. E-mail: [email protected].
Intelligent Decision-Making Systems In Smart Greenhouses, Muso Berdiyor Ugli Allanov
Chemical Technology, Control and Management
Smart greenhouses offer a solution to sustainable food production under climate uncertainty, yet their management often depends on fixed rules or human intuition. This study proposes an intelligent decision-making framework that integrates optimization, simulation, and a neural set into a self-learning system. By generating “conditionally real data” through simulation and evolutionary algorithms, the system can predict microclimatic changes and optimize control of water, energy, and nutrients. Continuous digital feedback enables adaptive, data-efficient operation even with limited real data. Experimental results demonstrate reduced resource use and improved yield stability, advancing the development of autonomous and resilient greenhouse ecosystems.
The Use Of Diagnostic And Restructuring Methods To Build Reliable Management Systems,
2025
Tashkent State Technical University. Address: 2 Universitet st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +998-90-325-85-55.
The Use Of Diagnostic And Restructuring Methods To Build Reliable Management Systems, Khurshid Salim Ugli Turayev
Chemical Technology, Control and Management
This article is devoted to the applied analysis of diagnostic and restructuring methods aimed at ensuring the reliability of control systems in the event of failures. The paper considers practical implementations of diagnostic and control algorithms using a servo drive setup as an example. The results of experiments are presented, demonstrating the system's behavior under various fault conditions. A comparative analysis of the effectiveness of the proposed solutions is carried out in terms of stability and operational accuracy. The obtained data confirm the feasibility of using adaptive control structures to increase the fault tolerance of technical systems. The article concludes …
Modern Significance And Development Trends In The Production Of Vegetable Oils,
2025
Tashkent State Technical University. Address: 2 Universitet st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +99897-430-13-76.
Modern Significance And Development Trends In The Production Of Vegetable Oils, Umidjon Ruziev, F.O. Qosimov, M.K. Shodiev
Chemical Technology, Control and Management
This article provides a comprehensive analytical review of the current state of the global vegetable oil production market. It describes the diversity of raw materials supplied, which includes both traditional and emerging fat sources. The paper also describes the technological stages of production, emphasizing modern innovations that contribute to more efficient, high-quality, and safe production. The article also covers global trends by comparing production dynamics between countries, highlighting regions with the highest rates of production growth and explaining the reasons for their competitive advantages. Particular attention is paid to environmental and socio-economic aspects, including sustainable land use, certification, carbon footprint, …
Investigation Of The Fuel Combustion Process In Gas-Fired Furnaces For Automation Systems,
2025
Tashkent State Technical University. Address: 2 Universitet st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected];
Investigation Of The Fuel Combustion Process In Gas-Fired Furnaces For Automation Systems, N.R. Yusupbekov, Sh.M. Gulyamov, A.T. Rajabov, U.U. Kholmanov
Chemical Technology, Control and Management
The regularities of the combustion process of gaseous fuel in chamber furnaces are described. This process represents a homogeneous reaction in which there is no distinct boundary surface between the fuel and the oxidizer. It is shown that the latter either mix and then burn subsequently, or both processes occur simultaneously, corresponding respectively to kinetic and diffusion combustion. The structure of a turbulent-diffusion flame of gaseous fuel combustion is presented.
Development Of Fire Prediction And Prevention Digital System Algorithms,
2025
Tashkent state agrarian university, Tashkent, Uzbekistan. E-mail: [email protected].
Development Of Fire Prediction And Prevention Digital System Algorithms, Oybek Zokirovich Koraboshev
Chemical Technology, Control and Management
This research work is devoted to the development of algorithms for a digital system aimed at early detection, prediction and prevention of fire hazards. In the work, the process of fire hazard assessment is modeled on the basis of modern information technologies and artificial intelligence tools. The main focus is on collecting data in real time, analyzing it and creating algorithms that determine the level of danger. In the process of research, methods of data cleaning, normalization and determination of correlation between variables were used to process multidimensional data streams obtained from various sensors (temperature, smoke, gas concentration and humidity …
Intelligent Method Of Dynamic Control For A Class Of Stochastic Nonlinear Systems,
2025
Tashkent State Technical University named after Islam Karimov. Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +998-88-700-52-68;
Intelligent Method Of Dynamic Control For A Class Of Stochastic Nonlinear Systems, Isamidin Khakimovich Siddikov, Davronbek Abdalimovich Khalmatov, Gulchekhra Rakhimjanovna Alimova, Dilnoza Rakhmanovna Khushnazarova
Chemical Technology, Control and Management
The paper considered the problems of researching the stabilisation system and backstepping control of stochastic nonlinear systems. The characteristics of stochastic nonlinear dynamic control systems are random signals with normal lawful distribution, which significantly complicates task control. In stochastic control, it is necessary to determine the trajectories of the control variables in order to achieve the desired control objective at minimum cost. Since the mathematical equations of stochastic nonlinear systems are not always constant, not every model-based controller can be accurate. Therefore, in this work, a neuro-fuzzy network is used to evaluate the parameters of the control system with backstepping, …
Reinforcement Learning In A Virtual World: A Study Of Ppo And Sac Within Unity Ml Agents,
2025
Azerbaijan State Oil and Industry University. Address: Azadliq Avenue 34, AZ1010, Baku, Azerbaijan E-mail: [email protected].
Reinforcement Learning In A Virtual World: A Study Of Ppo And Sac Within Unity Ml Agents, Rufat Mammadzada
Chemical Technology, Control and Management
This study explores the use of Unity3D as a versatile platform for developing, training, and evaluating intelligent agents through reinforcement learning. Leveraging the Unity ML-Agents Toolkit, a dynamic 3D environment was created to examine agent learning behavior using two advanced algorithms: Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC). The simulation environment consisted of navigable terrain bounded by red borders, with collectible blue balls serving as rewards and a purple cube representing the agent. A carefully designed reward system was implemented to encourage goal-directed behavior and penalize inefficiency, while time constraints introduced an additional challenge requiring both precision and speed. …
Meshless Discrete Velocity Boltzmann Model For Porous Media Flow,
2025
Embry-Riddle Aeronautical University
Meshless Discrete Velocity Boltzmann Model For Porous Media Flow, Amandine Maidenberg
Doctoral Dissertations and Master's Theses
This dissertation explores the combination of two sophisticated techniques for addressing computational fluid dynamics: the discrete velocity Boltzmann equation (DVBE) and the localized collocation meshless model with upwinding (U-LCMM). The DVBE is a high-level model that describes the foundations of transport phenomena by addressing the microscale motions of particles themselves and the effect of their aggregate behaviors on continuum principles. This equation integrates multiple scales of phenomena; while it can be used for fluid flow at Navier-Stokes scales, it can also resolve fine features that can only be described at the molecular level. This type of model is necessary for …
Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters,
2025
Tashkent State Technical University, Address: 100095, Tashkent city, st. University 2, Republic of Uzbekistan.
Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters, N.R. Yusupbekov, Yu.Sh. Avazov, G.Kh. Rashidov
Chemical Technology, Control and Management
This scientific article investigates the problem of analyzing technological process parameters in the fields of chemistry, energy, and metallurgy based on sensor data and applying intelligent signal processing methods. The main objective is to evaluate the effectiveness of artificial intelligence and deep learning models for intelligent analysis, forecasting, and anomaly detection of data obtained from sensors. Time-series data collected from industrial sensors were analyzed using LSTM (Long Short-Term Memory) and Autoencoder neural networks, as well as the Kalman filter. At the first stage of the study, sensor signals were denoised and their true state was estimated using the Kalman filter. …
Increasing The Robustness Of A Control System For A Complex Dynamic Plant By Correcting Nonlinearity In The Warping Process,
2025
Tashkent institute of textile and light industry
Increasing The Robustness Of A Control System For A Complex Dynamic Plant By Correcting Nonlinearity In The Warping Process, Tukhtamurod Khayitmurodovich Avezov, Zokhid Ergashboyevich Iskandarov
Chemical Technology, Control and Management
The paper discusses the challenges of enhancing the robustness of a control system for a complex dynamic plant by addressing nonlinearity in the warping process. Devices that ensure the stability of the control system against parameter non-stationarity on the warping machine are referred to as state controllers. The operating principle of these devices relies on providing artificial nonlinearity to the rear connection circuit of the control system's actuator. However, this nonlinearity is implemented using components that consider the parameters of low control quality. Therefore, it is necessary to continuously adjust the nonlinearity parameters to, on one hand, reduce the load …
Evaluation Of Deep Learning Techniques In Road Sign Recognition,
2025
Azerbaijan State Oil and Industry University. Address: Azadliq Avenue 34, AZ1010, Baku, Azerbaijan. E-mail: [email protected];
Evaluation Of Deep Learning Techniques In Road Sign Recognition, Latafat Abbas Gardashova, Haji Fakhraddin Hajiyev
Chemical Technology, Control and Management
Deep learning has transformed the computer vision field and greatly improved the performance and efficiency of road sign recognition systems. This research compares different deep learning methods, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and hybrid models, in terms of their ability to effectively detect and classify road signs under various conditions. The study compares performance measures such as accuracy, processing speed, and robustness to environmental conditions like low lighting, occlusion, and adverse weather. The results show that CNN-based methods, especially those with transfer learning and ensemble techniques, have better performance in real-time scenarios. Problems like computational …
Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems,
2025
Tashkent State Technical University, Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +998901092908.
Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems, Elbek Ortiqov
Chemical Technology, Control and Management
This article investigates various methods and tools for self-monitoring and fault tolerance in flow measurement transducers used in industrial processes. The study focuses on key techniques such as the use of redundancy, generation of reference values, analysis of measurement signals, and control of disturbance variables. These methods allow transducers to detect potential faults, ensure reliable operation, and maintain measurement accuracy even under adverse conditions. The article highlights how self-monitoring contributes to improving system safety, increasing reliability, and reducing downtime. It also discusses the integration of intelligent monitoring systems that support predictive maintenance and real-time diagnostics. Fault-tolerant sensors with self-monitoring capabilities …
Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods,
2025
Azarbaijan State Oil and Industry University. Adress: Azadliq Avenue, 34, Baku city, Republic of Azerbaijan. E-mail: [email protected], Phone:+994-51-706-45-25.
Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli
Chemical Technology, Control and Management
The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …
