Modeling Of Control Systems Research Articles

Artificial intelligence driven cyberattack detection system using integration of deep belief network with convolution neural network on industrial IoT

In Industry 4.0, information and communication technology (ICT) was employed in numerous significant infrastructures, like financial networks, smart factories, and power plants, to automate and certify industrial systems. In power control systems, ICT technologies such as IIoT have improved automated monitoring, but legacy methods, originally autonomous, now connect with external networks. This progress has presented safety vulnerabilities from legacy ICT systems. Hence, various cybersecurity approaches are developed and examined to deal with cyberattacks and vulnerabilities. Utilizing new cybersecurity models in power control systems poses risks due to their uncertified safety. Ensuring their stability and efficiency is significant for maintaining reliable power delivery and incorporating these technologies into power control systems. Therefore, this study designs a Next–Generation Cybersecurity Attack Detection using an ensemble deep learning model (NGCAD-EDLM) technique in the IIoT environment. The main cause of the NGCAD-EDLM technique is the automatic recognition of cyber-attacks. In the NGCAD-EDLM approach, the primary data normalization phase utilizing min-max normalization is performed. Next, the honey-badger algorithm (HBA) approach selects the feature subsets. Furthermore, an ensemble deep learning (DL) of two methods, namely convolutional neural networks (CNNs) and deep belief networks (DBNs) methods, are employed for classification. In addition, the DL techniques' hyperparameter selection is accomplished using the lotus effect optimization algorithm (LEOA) method. A complete set of simulation validation is performed to establish the experimental analysis of the NGCAD-EDLM method. The performance validation of the NGCAD-EDLM method exhibited a superior accuracy value of 99.21 % over other existing techniques.

Исследование многоуровневых моделей управления вагонопотоками в адрес припортовых станций с применением теории дифференциальных уравнений

Purpose: To consider the issue of sustainability of multi-level control systems for car flows to port railway stations in the conditions of intellectualization of transportation management processes. To assess the influence of three-level and two-level control systems for the operational work of port roads on the quality of planning the supply of trains to port stations under various modes of operational operation of railways. Determine the conditions for the stability of the car flow control system by constructing and studying the corresponding hard and soft mathematical models described by autonomous systems of ordinary linear differential equations. Methods: In this study, the methods of the theory of stability of solutions of differential equations, as well as the theory of control and dynamical systems are used. A phase space is used in a visual representation, a qualitative and quantitative analysis of the behavior of phase trajectories in it is performed, corresponding to undisturbed and perturbed solutions of systems of differential equations describing the constructed models of control systems. Results: A comparison of the characteristics of multistage car traffic control systems is given. A study of the stability of multilevel models of car traffic management in the context of the intellectualization of management functions is proposed. In the environment of the analytical computing system, the conditions of asymptotic stability in time of a two-level wagon traffic control system are found and studied. Practical importance: The results obtained by computational experiment make it possible to assess the stability of the functioning of port-side transport and technological systems in the context of changes in the organization of production and the intellectualization of transportation management processes. Computer mathematics systems make it possible to implement the heuristic component of research and obtain theoretically sound and visual solutions to problems of optimizing cargo and wagon traffic control modes.

PCR virtual temperature sensor design based on system modeling and identification

The reaction results of Polymerase chain reaction (PCR) are highly sensitive to temperature accuracy, but the reaction liquid temperature is hard to be measured directly. In this paper, a virtual temperature sensor is creatively designed to directly obtain the reaction liquid temperature using a model-switching approach. This study first establishes the mathematical models of the temperature control system and obtains precise system models for the heating and cooling stages. Based on this, a virtual sensor is constructed, and a closed-loop fuzzy PID control system is established. Furthermore, the accuracy of the designed virtual temperature sensor is verified through simulation and experimentation. Simulation results show that the fuzzy PID control method has higher temperature accuracy, with a deviation of 0.23 °C, making it more suitable for Peltier systems, as Peltier systems suffer from inconsistent temperature rise and fall models. The experimental results show that the control method using the virtual sensor achieves higher precision in liquid temperature control, with an accuracy of ±0.21 °C. Finally, standard PCR procedures are performed for designed chip, and the results indicate that the temperature sensor and control system designed in this study exhibit significantly higher amplification efficiency, approximately 16 times greater than traditional control methods.

A review of integrated modeling and simulation of control and communication systems in Smart Grid

In order to provide effective, safe, and dependable grid operation, the use of information and communication technologies (ICT) for real-time monitoring and control of the Smart Grid (SG) has grown in recent years. With such technologies, our system evolved into a complex cyber-physical system (CPS) in which communications networks play an important role in the dynamic performance of SG. Therefore, it is imperative to perform integrated modeling and simulation (IMS) of control and communication systems to evaluate the SG CPS for new control strategies or select appropriate communication technologies for specific applications before implementing them on a larger scale. This paper provides a state-of-the-art literature review about co-simulation, one of the key methods to perform an IMS. The paper starts with a brief review of the SG communication infrastructure, communication, and SG simulators used for co-simulations to give the readers an understanding of the requirements and issues for modeling and simulating SG communication systems. Then, detailed literature about the co-simulation platform covers the individual simulators used, the key features, test case advantages, and the limitations of different co-simulation platforms. In the discussion section, comparative analyses of co-simulation platforms are provided. The review summarizes critical challenges and opportunities in co-simulation, emphasizing the potential of IMS for advancing SG design and operation.

Systematic solution for multi-model control approaches in nonlinear dynamic systems based on the s-gap metric

This paper proposes a systematic approach for optimizing the distribution of local models in multi-model control systems (MMCS) to enhance overall robustness. While existing literature discusses this method for linear parameter varying (LPV) and uncertain linear time-invariant (LTI) systems, significant limitations persist in addressing nonlinear dynamic systems. Robust control tools like the gap metric and generalized stability margin (GSM) have limited effectiveness in analyzing the robustness of nonlinear feedback systems. To address these challenges, novel concepts of the gap metric and GSM are introduced to determine central operating points (COPs) within local operating areas (LOAs) across the total operating area (TOA). These COPs guide the extraction of affine disturbance local models (ADLMs). Additionally, an optimization problem based on the s-gap metric and GSM is presented to optimize COPs placement and LOAs boundaries. Challenges such as non-monotonic behavior of the cost function and complexity arising from the s-gap metric formulation necessitate novel solution methods. To address these, constraints are applied to the cost function, and a novel discrete optimization approach is introduced. Finally, theoretical findings are applied to the Duffing system, pH neutralization process, and continuous stirred tank reactor (CSTR) plant to evaluate the proposed method's effectiveness. This comprehensive validation across different systems underscores the versatility and practical utility of the proposed approach.

Conceptualization of Intelligent Control System for Humanitarian Demining Robotic Complexes Based on Verbal Methods

Introduction. Humanitarian demining is characterized by growing attention to the problems of creating and using robotic systems. The most important aspect of their use is the control method.Problem Statement. At present, the fi rst generation robotic complexes (controlled devices) have been the mostcommon, the second generation complexes (semi-autonomous devices) have been improving. To switch to the third generation complexes (autonomous devices), it is necessary to develop intelligent control systems based on artificial intelligence technologies. The most used for system development are quantitative methods, but such models are “black box models” that do not provide complete clarity about their behavior.Purpose. To develop conceptual model of intelligent control systems for humanitarian demining robotic complexes based on verbal methods.Materials and Methods. Formal logic methods, verbal analysis qualitative methods, and BPMN. Results. Conceptual model of intelligent control systems for humanitarian demining robotic complexes and sym bolic models of representing relevant declarative and procedural knowledge based on verbal methods have been developed.Conclusions. The conceptual model makes it possible to formulate Symbolic Models in the notations of selected verbal methods. At the decision-making level, the ordinary classifi cation method by denotation of the terms used by experts in the selected subject area has been chosen. At the executive level, the BPMN method has been chosen to create process diagrams in graphical notation. The verbal methods make it possible to create “white-box models” that unambiguously interpret the dependence of output and input variables and to explain the model behavior. Symbolic models in the notations of selected verbal methods allow the implementation of an intelligent control systems for a specifi c humanitarian demining robotic complex.

Application of fuzzy approach to control systems modeling of the mobile robot

In the article, the principles of construction and modification of the PID regulator were considered and the following results were obtained. In order to improve the characteristics of classical PID controllers, free and filter controllers have been applied to construct signals. The principle of open control given in PID regulators allows to reduce the regulation time and increase the stability reserve of the system, and also compensates for external effects. Fuzzy logic in PID controllers is mainly used in two ways: for the construction of the controller itself and for organizing the tuning of the coefficients of the PID controller. Both methods can be used simultaneously.

Design and Test of Intelligent Farm Machinery Operation Control Platform for Unmanned Farms

The unmanned farm control platform is of great significance in promoting the supervision of farm production with less manpower or autonomous operation of farm machinery and the construction of farm informatization. Addressing the existing control platform for farm location information acquisition is time-consuming, labor-intensive, and lacks the whole process control of multiple types of farm machinery. In this paper, we propose an Internet of Things (IoT) control scheme for intelligent farm machinery operation of unmanned farms and design the access standards for multiple types of farm machinery, as well as realize the remote control of intelligent farm machinery operation by constructing a remote control model. A high-precision map construction method is designed to improve the DeepLabV3+ algorithm to identify fields and roads. The control models of path planning, remote task, remote control, and safety system are built to achieve the remote control of intelligent agricultural machinery operation. The proposed technology is implemented in the platform integration and application tests are carried out. The error of the constructed high-precision map is less than 3 cm, the completeness rate of the automatic boundary extraction rate is 96.71%, and the correctness rate is 95.63%, which can be used to obtain the boundary instead of manual labeling or on-site point picking. The use of the platform for the simultaneous control of three farm machinery operations reduces the number of people in operation and production and reduces the professional requirements of the personnel, which will promote the management of the entire farm by one person or even by no one in the future.

Finite-step alternating approximately bi-similar symbolic model for Markov jump systems

Establishing a bi-similar abstraction (symbolic model) of control systems has been demonstrated as a viable approach for implementing temporal logic tasks on control systems. Previous research primarily focused on logic tasks over an infinite time horizon. However, practical scenarios often involve control tasks defined within finite time intervals. Hence, this paper addresses the finite-time bi-similar problem specifically for a significant class of stochastic switched systems known as Markov jump systems (MJSs). To achieve this, two novel concepts are introduced: finite-time stochastic incremental stability (FSIS) and finite-step alternating approximate bi-simulation relation. A sufficient condition is firstly established for FSIS of MJSs by leveraging the incremental weak infinitesimal operator. Subsequently, a symbolic model is developed for MJSs by employing gridding techniques. Furthermore, a sufficient condition is derived to ensure that the developed symbolic model exhibits finite-step alternating approximate bi-similarity with the original MJSs. Finally, two numerical examples illustrate the application of the proposed results.

АНАЛИТИКА ПАРАМЕТРОВ САЛИВАРНОГО СТАТУСА СТУДЕНТОВ-КУРИЛЬЩИКОВ ПРИ ИСПОЛЬЗОВАНИИ СПРЕЯ С МУКОПРОТЕКТОРОМ

Subject. The subject of this study is the salivary status in the patients.
 Objectives. The objective is to identify specifics of data analytics of the salivary status in student smokers effected by using a mucoptorotective dental spray. 
 Methodology. The study is made by the Ural State Medical University Department of Preventive Dentistry and Propedeutics of Dental Disease, the Ural State Medical University Department of General Chemistry, the Ural Federal University Department of Control Systems Modeling. The objects of the study are unstimulated mixed saliva and a mucoptorotective spray that helps to protect the oral mucosa against inflammations, facilitates penetration across epithelial membranes, acts as a controlled multifunctional drug delivery system for parodontium tissues. The two study groups were formed from 20 volunteers in the age of 20 to 24 years old (4 women and 36 men, the average age was 22,35 years old): the first (main) group consisted of smoking patients, the second (reference) group consisted of non-smokers. The clinical assessment of the oral cavity of patients included: analysis of complaints, analysis of anamnesis, examination, evaluation of the hygiene index (OHI, Greene, Vermillion, 1964), dental caries severity index (using DMFT and DMFS indices), the state of gingival inflammation, PMA index (Parma). Unstimulated mixed saliva was studied, the quantitative analysis of the secretion was made by analyzing color, transparency, presence of inclusions, pH value, the functional activity of minor salivary glands. The statistical analysis of results was made using a PC with Microsoft Excel 2007 software program; the statistical significance was assessed using Student’s t-distribution by Statistica 6.0 software package.
 Conclusions. Given the reduction of objective values of index assessment of oral health status used as indicators of changes in oral health, the study of the data analytics of salivary status in student smokers in the course of using a mucoptorotective spray revealed the harmful effects of tobacco on salivary composition and parameters. The findings prove smoking-related oral homeostatic disruption promoting development and progression of dental diseases of the hard tissues, parodontium, oral mucosa. Application of the dental spray with titanium glycerosolvate aquacomplex is proved to be an effective way to prevent development and progression of such diseases.

Review Work on Modelling & Simulation of Car Cruise Control System using PID Controller

This work focuses on the modeling and simulation of car cruise control systems with the implementation of a Proportional-Integral-Derivative (PID) controller. The primary objective is to develop a comprehensive model that integrates a PID controller for maintaining car speed under varying conditions. The methodology involves detailed modeling techniques to simulate car dynamics and the tuning of PID parameters for optimal control

Three-model-driven fault diagnosis method for complex hydraulic control system: Subsea blowout preventer system as a case study

Hydraulic control is a control pattern that uses compression fluid as the energy medium and information medium. Hydraulic system is widely used in the control of industrial systems because of its flexibility and reliability. Hydraulic systems have the characteristics of strong fault concealment, significant sensor delay, and a complex signal transmission mechanism. Hence, it is very difficult to identify the faults of systems under the influence of powerful nonlinear time-varying characteristic. The diagnosis of complex hydraulic control system is a problem facing the current research. In order to cope with the challenges caused by limited sensors and concealment of faults, a three-model-driven fault diagnosis method is proposed for complex hydraulic control system. The three hydraulic control system models with regard to energy, fluid and information are proposed and established to explain the work process of the system from different perspectives. The diagnostic model is completed by establishing a fault reasoning model based on the Bayesian network. A redundant control system for subsea blowout preventer is used as a case to demonstrate the proposed method, and the results show that the proposed method has high accuracy.

Flight-Data-Based High-Fidelity System Identification of DJI M600 Pro Hexacopter

Research and industrial application can require custom high-level controllers for industrial drones. Thus, this paper presents the high-fidelity dynamic and control model identification of the DJI M600 Pro hexacopter. This is a widely used multicopter in the research and industrial community due to its high payload capability and reliability. To support these communities, the focus of control model identification was on the exploration and implementation of DJI Onboard Software Development Kit (OSDK) functionalities, also including some unconventional special modes. Thus, the resulting model can be controlled with the same OSDK functionalities as the real drone, making control development and application time effective. First, the hardware and software structure of the additional DJI M600 onboard system are introduced. Then, the postulated dynamic and control system models are shown. Next, real flight test campaigns generating data for system identification are presented. Then, the mass and inertial properties are estimated for TB47S and TB48S battery sets and the custom Forerunner UAV payload. Dynamic system model identification includes the aerodynamic effects and considers hover, vertical, and horizontal forces together with static horizontal wind components and finally the rotational moments and dynamics. The control system components were identified following the structure of OSDK, including vertical, horizontal, and yaw loops. After identification, the model was validated and refined based on an unused flight test and software-in-the-loop simulation data. The simulation is provided by DJI and was also compared to real flight results. This comparison showed that the DJI simulation covers the dynamics of the real drone well, but it requires being connected to the drone and needs the controllers onboard to be implemented in advance, which limits applicability and increases development time. This was another motivation to introduce a standalone simulation in Matlab Simulink, which covers all the important modes of OSDK control and can be run solely in Matlab without any hardware support. The constructed model will be published for the benefit of the research and industrial community.

Structuring of management control systems by resident organizations in technological parks

Purpose: The present research emphasizes the models of management control system (MCS), with the objective of analyzing the structuring of Guamá Science and Technological Park companies MCSs, allowing to measure the level of structuring of their management processes.
 Methodology: This is exploratory research developed with a quantitative approach, through a survey, applied in 15 enterprises at Guamá Science and Technological Park.
 Results: The results indicated that resident entrepreneurs have structured management control systems, with greater emphasis on planning markers and results control and less structuring of cultural and behavioral controls, in line with the results obtained with the importance attributed by managers to the use of MCS. It was concluded that the companies participating in the research conduct a balanced management between planning and operational control, with the need to conduct actions to stimulate the use of management tools that help in dissemination of culture and behavioral controls.
 Contributions of the Study: As a practical contribution, this study contributed to improvement of technological Parks management, from the mapping of the needs of their users. As an academic contribution, we believe that understanding management factors that are best developed and those that need to be developed to achieve satisfactory levels of management control systems is critical for definition of internal development policies of management processes, thus, moving forward for the social contribution of the research, the theoretical improvement favors entrepreneurs and their ventures, with profits for ecosystem of technological parks and for general society.

Laboratory Equipment for Modeling, Analysis, Design, and Implementation of Control Systems in Engineering

Laboratory Equipment for Modeling, Analysis, Design, and Implementation of Control Systems in Engineering

Intelligent vector-frequency control system for asynchronous electric motors

This article analyzes the main directions and principles of developing a mathematical model for creating an intelligent system for vector-frequency control of asynchronous electric motors. Particular attention is paid to the development of a frequency converter structure that allows the implementation of an energy-saving algorithm in a direct torque control (DTC) system to reduce stator current consumption from the power source. This approach guarantees stable operation of the electric motor under various load conditions and voltage changes in the electrical network. The synthesis of a speed control system and current control loops are considered and generalized models of a vector control system are developed using the Matlab software package and the main Simulink library.

Логико-временная формализация имитационных моделей систем железнодорожной автоматики и телемеханики

The purpose of the article is to present the results of developing a method for formalizing simulation models of railway automation and remote control systems as queuing systems with a rigidly regulated sequence of using service devices while processing streams of requests of various types. For the software implementation of simulation models with such properties, the GPSS World tool is traditionally used. The logical time formalization is proposed, and the concept of the proposed formalization of simulation models is formulated. Its main provisions include: the type of request is determined solely by the composition and sequence of occupation and release of servicing devices; the use of transaction parameters to organize their multiphase processing for each type of request; checking the value of Boolean functions for each procedure of processing requests for each type; the regulated time in the procedure of processing requests is considered as one of the many logical conditions of Boolean functions; logical and parametric description of the modeled system should be performed at the level of initial data without changing the text of the modeling program. Objects in GPSS World sufficient for implementing this concept have been identified. Using the selected objects, an alphabet has been compiled, and logical diagrams of modeling algorithms have been developed in the obtained alphabet. This serves as a demonstration of the application of the logical time concept for the formalization of simulation models of complex queuing systems. A GPSS program has been developed to confirm the possibility and feasibility of using the proposed method for formalizing simulation models of railway automation systems with a rigid structure.

Quantitative Robustness for Signal Temporal Logic With Time-Freeze Quantifiers

Signal Temporal Logic (STL) is a variant of Metric Temporal Logic (MTL) which can express intricate temporal requirements over signals, and has found wide adoption for expressing requirements over complex control systems models. A key factor in the success of STL has been that of quantitative robustness, and the development of efficient algorithms for computing the robustness values over traces. The real-valued quantitative robustness of a signal with respect to an STL property quantifies the degree of satisfaction or violation of the property by the signal. In this work we introduce a notion of robustness for a more expressive logic, Timed Signal Temporal Logic (TSTL), which can be seen as Timed Propositional Temporal Logic (TPTL) with predicates defined over real-valued signals. This logic can express many natural engineering requirements that STL cannot. We also develop algorithms for computing this robustness value over traces in the pointwise semantics. While the robustness computation for general TSTL formulae is PSPACEhard due to the PSPACE-hardness of the monitoring problem for TPTL, for the special case of one variable TSTL, a fragment of TSTL which is still more expressive than STL, we develop an optimized algorithm which computes robustness in time linear in the length of the trace. Finally, we experimentally validate the tractability of our algorithms with our prototype tool in Matlab.

АНАЛИЗ ОСВОЕНИЯ МАНУАЛЬНЫХ НАВЫКОВ РЕСТАВРАЦИИ МОЛЯРОВ СТАРШЕКУРСНИКАМИ СТОМАТОЛОГИЧЕСКОГО ФАКУЛЬТЕТА

Subject. The subject of this research is manual skills in molar restoration.
 Objective. The objective of this research is to analyze the process of mastering manual skills in restoration of phantom molar tooth models by senior dental students.
 Methodology. The study was carried out by the Department of Therapeutic Dentistry and Propedeutics of Dental Disease of Ural State Medical University of the Ministry of Health of the Russian Federation together with the Department of Control Systems Modeling, Ural Federal University. The study involved 54 four- and five-year dental students of Ural State Medical University (24 young male adults, 30 young adult women; the average age was 22.25 ± 1.75 years) in a procedure of dental filling of carious cavities in five “phantom” teeth – extracted molars (Black classification was Class I). This research applied the method developed by Prof. Larisa Lomiashvili together with co-authors for molar restoration using modular techniques. To analyze self-assessment of manual skills for molar restoration by senior students the questionnaire was completed. The questionnaire was made up of three blocks including 12 questions (parameters) evaluated using 1 to 10 rating scale survey, the rating being 10 for “fully satisfied”, and 1 for “completely dissatisfied”. The survey questions were divided into the following blocks: understanding of dental anatomical features, professional skills of students, cognitive motivational factors.
 Conclusions. The analysis of assessment scores and survey responses showed that mastering manual skills by senior students during a molar restoration procedure promotes their accuracy and ability to work with precision. The analysis of mastering manual skills for molar restoration by dental senior students using the survey responses showed rather high self-assessments (p ≤ 0.05).

Longer duration entry mitigates nystagmus and vertigo in 7-Tesla MRI.

Patients and technologists commonly describe vertigo, dizziness, and imbalance near high-field magnets, e.g., 7-Tesla (T) magnetic resonance imaging (MRI) scanners. We sought a simple way to alleviate vertigo and dizziness in high-field MRI scanners by applying the understanding of the mechanisms behind magnetic vestibular stimulation and the innate characteristics of vestibular adaptation. We first created a three-dimensional (3D) control systems model of the direct and indirect vestibulo-ocular reflex (VOR) pathways, including adaptation mechanisms. The goal was to develop a paradigm for human participants undergoing a 7T MRI scan to optimize the speed and acceleration of entry into and exit from the MRI bore to minimize unwanted vertigo. We then applied this paradigm from the model by recording 3D binocular eye movements (horizontal, vertical, and torsion) and the subjective experience of eight normal individuals within a 7T MRI. The independent variables were the duration of entry into and exit from the MRI bore, the time inside the MRI bore, and the magnetic field strength; the dependent variables were nystagmus slow-phase eye velocity (SPV) and the sensation of vertigo. In the model, when the participant was exposed to a linearly increasing magnetic field strength, the per-peak (after entry into the MRI bore) and post-peak (after exiting the MRI bore) responses of nystagmus SPV were reduced with increasing duration of entry and exit, respectively. There was a greater effect on the per-peak response. The entry/exit duration and peak response were inversely related, and the nystagmus was decreased the most with the 5-min duration paradigm (the longest duration modeled). The experimental nystagmus pattern of the eight normal participants matched the model, with increasing entry duration having the strongest effect on the per-peak response of nystagmus SPV. Similarly, all participants described less vertigo with the longer duration entries. Increasing the duration of entry into and exit out of a 7T MRI scanner reduced or eliminated vertigo symptoms and reduced nystagmus peak SPV. Model simulations suggest that central processes of vestibular adaptation account for these effects. Therefore, 2-min entry and 20-s exit durations are a practical solution to mitigate vertigo and other discomforting symptoms associated with undergoing 7T MRI scans. In principle, these findings also apply to different magnet strengths.