Reliability Of Control System Research Articles

Contribution to a New Algorithm to Perform an Automatic Self-Calibration of Current Sensors

Abstract Sensors calibration plays a crucial role in controlling systems and achieving fault-tolerant control by ensuring accuracy, performance, safety, energy efficiency, and compliance with standards. It is an essential to maintain the reliability and effectiveness of modern control systems across various applications. In this paper, we represent a new algorithm that processes a set of raw data collected by a sensor to find the mapping function that relates the raw data to the real value of the measured signal by the sensor. Working on sensors with an unknown mapping function, unknown parameters, or with external disturbances, that affects their behaviour, represents a problem; moreover, it takes a lot of time and effort to calibrate the sensor before each use. Several techniques were used to overcome these aspects mostly by recording the output of the sensor for different input values that change manually, to calibrate the sensor. However, the represented technique in this paper can easily provide us with the input/output model of a specific sensor by doing only one experiment; it also improves the accuracy of the measurements as it is a self-calibrating technique that reduces the nonlinearity and noise problems to deliver a better estimation of the measured signal, which is validated in this paper experimentally using a low-cost current sensor by comparing the obtained results from this algorithm with the results using the extracted input/output model illustrated in the datasheet. Furthermore, if the sensor is pretty poor, and if the application requires more precision, the provided estimation by the mapping function can be mixed with other sensor/s readings using sensor fusion algorithms to find a more precise value of the input. The represented algorithm can also perform self-calibration while evaluating the functionality of the application and the variations of the temperature and other external disturbances that affect the sensor.

A prostate seed implantation robot system based on human-computer interactions: Augmented reality and voice control.

The technology of robot-assisted prostate seed implantation has developed rapidly. However, during the process, there are some problems to be solved, such as non-intuitive visualization effects and complicated robot control. To improve the intelligence and visualization of the operation process, a voice control technology of prostate seed implantation robot in augmented reality environment was proposed. Initially, the MRI image of the prostate was denoised and segmented. The three-dimensional model of prostate and its surrounding tissues was reconstructed by surface rendering technology. Combined with holographic application program, the augmented reality system of prostate seed implantation was built. An improved singular value decomposition three-dimensional registration algorithm based on iterative closest point was proposed, and the results of three-dimensional registration experiments verified that the algorithm could effectively improve the three-dimensional registration accuracy. A fusion algorithm based on spectral subtraction and BP neural network was proposed. The experimental results showed that the average delay of the fusion algorithm was 1.314 s, and the overall response time of the integrated system was 1.5 s. The fusion algorithm could effectively improve the reliability of the voice control system, and the integrated system could meet the responsiveness requirements of prostate seed implantation.

Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.

Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate interpretation of human intentions for both efficiency and safety. Electroencephalogram (EEG) signals, commonly employed to measure brain activity, offer a direct communication channel between humans and robotic arms. However, the ambiguous and unstable characteristics of EEG signals, coupled with their widespread distribution, make it challenging to collect sufficient data and hinder the calibration performance for new signals, thereby reducing the reliability of EEG-based applications. To address these issues, this study proposes an iteratively calibratable network aimed at enhancing the reliability and efficiency of EEG-based robotic arm control systems. The proposed method integrates feature inputs with network expansion techniques. This integration allows a network trained on an extensive initial dataset to adapt effectively to new users during calibration. Additionally, our approach combines motor imagery and speech imagery datasets to increase not only its intuitiveness but also the number of command classes. The evaluation is conducted in a pseudo-online manner, with a robotic arm operating in real-time to collect data, which is then analyzed offline. The evaluation results demonstrated that the proposed method outperformed the comparison group in 10 sessions and demonstrated competitive results when the two paradigms were combined. Therefore, it was confirmed that the network can be calibrated and personalized using only the new data from new users.

Robust optimization of highly reliable automatic control systems

Robust optimization of highly reliable automatic control systems

COLSim, a simulator for Hybrid Navigation Acceptability and Safety

Autonomous vessels have emerged as a prominent and accepted solution. However, achieving full autonomy for marine vessels requires the development of robust and reliable mission planning and control systems that can handle various encounters with manned and unmanned vessels while operating effectively in various weather and sea conditions. These algorithms need to account for various aspects of a mission like global/local planning, manoeuvrability limitations, external disturbances, Collision Avoidance (COLAV), motion regulations. A significant challenge in this pursuit is ensuring the autonomous vessels’ compliance with the International Regulations for Preventing Collisions at Sea (COLREGs). This paper proposes a (prototypical) realisation of an open-source simulator including replay of AIS Data. The aim of this simulator is to provide fast simulation feeded with real data and including autonomous agents.

DEVELOPMENT OF NATURAL GAS EXCHANGE INFRASTRUCTURE: EUROPEAN EXPERIENCE AND UKRAINE

The aim of this paper is to summarise the conditions and problems of the development of the gas market exchange in European countries, and to identify the necessary elements for its successful functioning in Ukraine. Methodology. The study is based on the historical and logical methods of analysing the development of the infrastructure of energy exchanges in Germany, Austria, Italy, Romania and Poland. The paper uses empirical (observation, comparison) and theoretical (analysis, synthesis, systematisation, generalisation) research methods. In general, the years of analysis cover the period from 2007 to 2023 due to the launch of natural gas trading on the analysed exchanges. In order to analyse the dynamics and show the evolution of natural gas trading on the European energy exchanges, information on volumes and structure of the natural gas segment was collected from their annual reports, official press releases and newsletters for the years 2007-2021 (EEX and EEX Group), 2019-2022 (CEGH, also using Energy Community data), 2021-2022 (GME), 2020 (ANRE, TGE). To analyse the dynamics of the UEEX development, a sample of data for 7 years has been presented, collected from annual reports, press releases and additional sources of analytical data due to the lack of official data for some periods. In order to examine changes in the structure of UEEX natural gas trading volumes, monthly trading volumes for 2020-2023 were collected and grouped by short-term and medium- and long-term products. Results. This paper examines the importance of exchange trading in the natural gas market. Based on the experience of European countries, such as EEX in Germany, CEGH GE in Austria and GME in Italy, BRM in Romania, and TGE in Poland, it can be said that each country has its own characteristics and path to a liberal market. The German and Austrian cases showed that cooperation and integration inevitably lead to the growth of exchanges, as happened with the start of the PEGAS cooperation, when the Italian government-regulated exchange did not show such a rapid growth trend. Other elements that ensured the development of exchange trading in natural gas were identified: diversification of the market and commodity portfolios, improved clearing, a reliable control and accountability system, a combination of market mechanisms and state supervision, and the development of technology. It was concluded that Ukraine has the prerequisites and potential for the functioning of the natural gas market on a liberal basis. At the same time, there is a need to further develop the institutional environment for exchange trading, and the above elements could be areas for improvement. The practical implications are that an energy exchange is a key institution of a liberal gas market, and a strong exchange infrastructure ensures efficient trade and regional integration. Value/originality. The analysis of the experience of European countries allows to draw conclusions about the successful development of infrastructure and provide recommendations for the development of the Ukrainian energy exchange, as well as identify areas for the development of regulatory policy to ensure the successful launch of exchange trading in gas on national markets.

Prediction of Remaining Useful Life (RUL) of Electronic Components in the POSAFE-Q PLC Platform under NPP Dynamic Stress Conditions

In the Korean domestic nuclear industry, to analyze the reliability of instrumentation and control (I&C) systems, the failure rates of the electronic components constituting the I&C systems are predicted based on the MIL-HDBK-217F standard titled ‘Reliability Prediction of Electronic Equipment’. Based on these predicted failure rates, the mean time to failure of the I&C systems is calculated to determine the replacement period of the I&C systems. However, this conventional approach to the prediction of electronic component failure rates assumes that factors affecting the failure rates such as ambient temperature and operating voltage are static constants. In this regard, the objective of this study is to propose a prediction method for the remaining useful life (RUL) of electronic components considering mean time to failure calculations reflecting dynamic environments, such as changes in ambient temperature and operating voltage. Results of this study show that the RUL of electronic components can be estimated depending on time-varying temperature and electrical stress, implying that the RUL of electronic components can be predicted under dynamic stress conditions.

Control and management of microgrid clusters: development and future research

The paper explores the potential of microgrid clustering technology and its impact on addressing energy and environmental challenges. Over the past decades, there has been a significant interest in using microgrids to ensure stability and reliability in power systems, especially considering the increasing utilization of renewable energy sources. Microgrid clusters coordinate power distribution between microgrids and the main grid, effectively addressing issues such as voltage rise, harmonics, low power factor, power backflows, and deficiencies in protection schemes. However, before implementing microgrid clustering, certain challenges need to be overcome, particularly in terms of design considerations. The paper critically reviews the design challenges of microgrid clustering, highlighting the advantages and challenges that arise during the development of microgrids, especially the problem of inadequate adaptation to large-scale renewable energy sources. The research analyzes various architectures of microgrid clusters and methods of their interaction. The classification of microgrid clustering is based on different architectures according to connection locations. Additionally, a comparison of different power transmission technologies within microgrid clusters, such as alternating current and direct current systems, is conducted with an assessment of the advantages and disadvantages of each technology. Considerable attention is given to the control and management of microgrid clusters, elucidating the possibilities of hierarchical and distributed management structures to ensure optimal power distribution and voltage and frequency regulation. In conclusion, the paper examines promising directions for further research aimed at enhancing the integration of large-scale renewable energy sources, developing intelligent management and energy management systems, as well as establishing reliable control and management systems for microgrid clusters.

Optimal Control for a Three-Rotor Unmanned Aerial Vehicle in Programmed Flights

In this study, we propose a new approach to selecting PID controller parameters for a UAV tricopter during programmed flights. The approach uses optimization techniques to determine the optimal values of the PID controller parameters based on the desired performance of the UAV. The proposed method is particularly effective for repeated programmed flights in which the UAV follows a defined flight path. The use of a PID control provides a reliable and robust control system that can cope with various disturbances and uncertainties in UAV dynamics. The proposed method provides an alternative to adaptive control, which requires a significant amount of system identification and parameter tuning. The effectiveness of the proposed method has been verified in simulation studies, and the results show its ability to achieve satisfactory performance with low tracking error and fast response time. The result of the work is an improvement in control for a specific object at a specific mission. We present how the recipients can perform this procedure for their object and their mission to be able to improve the control gain in the physical controller.

Fault Detection and State Estimation in Automatic Control

Fault detection and state estimation play pivotal roles in ensuring the reliability, safety, and performance of automatic control systems [...]

DEVELOPMENT OF CONTROL LAWS OF UNMANNED AERIAL VEHICLES FOR PERFORMING GROUP FLIGHT AT THE STRAIGHT-LINE HORIZONTAL FLIGHT STAGE

The article proposes an improved approach to controlling groups of unmanned aerial vehicles (UAVs) aimed at increasing the overall efficiency and flexibility of the control process. The use of a heterogeneous external field, which varies both in magnitude and direction, allows achieving greater adaptability and accuracy in controlling a group of UAVs. A vector field for unmanned aerial vehicles determines the direction and intensity of the vehicles' movement in space. Such vector fields can be used to develop UAV control laws, including determining optimal flight paths, controlling speed, avoiding obstacles, and ensuring coordination of a group of UAVs. The subject of the study is the methods of controlling groups of autonomous UAVs, where each vehicle may have different speeds and flight directions. To solve this problem, various methods of using a heterogeneous field have been developed and proposed. Instead of using a homogeneous field that provides a constant flight speed, a vector field is used that adapts to different conditions and characteristics of the vehicles in the group. This method allows for effective group management, ensuring the necessary coordination and interaction between the vehicles. An analysis of recent research and publications in the field of autonomous system control indicates the feasibility of using machine learning, vector fields, and a large amount of data to successfully coordinate the movement of autonomous systems. These approaches make it possible to create efficient and reliable control systems. The aim of the study is to develop laws for controlling the movement of a group of autonomous unmanned aerial vehicles at the stage of straight-line horizontal flight based on natural analogues to improve the efficiency and reliability of their coordinated movement in different conditions. The main conclusions of the research are that the proposed method of controlling groups of UAVs based on a heterogeneous field can be implemented. It takes into account a variety of vehicle characteristics and environmental conditions that are typical for real-world use scenarios. This work opens up prospects for further improving the management of UAV groups and their use in various fields of activity. The article emphasises the relevance of technology development for autonomous unmanned systems, especially in the context of autonomous transport systems.

Hydrodynamics of transient processes in a well with an electric submersible pump

The relevance. Associated with the problem of increase in efficiency of algorithms for monitoring and controlling the dynamic operation modes of wells equipped with an electric submersible pump with adjustable supply. The result summarizes and develops the previously published solution on the design of a dynamic well model, through the transition from linearized correlations to quadratic relationships between states at key points of a lift. These points properly reflect the observed forms of behavior in transient and equilibrium operating modes at full start-stop control ranges. The main aim. Updated description of a comprehensive quadratic barometric model of the «reservoir–lift–electric pump–well head» type well, focused on the tasks of automatic control and regulation in real time. Objects. Well with frequency-regulated submersible pump. Methods. Material balance, percolation, hydrostatics, quadratic kinetics of friction losses, numerical modeling of differential equations, finite-dimensional description of the complex hydrodynamics of the well, taking into account the potential and kinetic head losses in the lift. Results: (1) Updated mathematical description of the hydrodynamics of the well with an electric submersible pump creates the basis for: more reliable solution of inverse problems of parametric model support according to the data of field control, refined assessment of the adjustment potential, predicting the dynamics of a possible system output beyond the boundaries of functional stability, technologies of numerical and analytical design of optimal solutions when selecting the parameters of arrangement and laws of operational regulation, synthesis of dynamic observers of an extended state vector synchronously operating with the dynamics of controlling well-head and deep pressure. (2) The results of the computational analysis demonstrate a complex behavior that does not match the graph of the inflow and pump supply, when changing the frequency and wellhead pressure. This explains the observed effect of the multi-tempoity of transient processes during starts and stops and possible instability of the supply with a sharp decrease in frequency. (3) Estimates of discrepancy between the solutions for a quadratic model and a linearized prototype indicate an increase in errors of linearized analysis with strong deviations of operating modes from the equilibrium-calculated states. The refinements in dynamically disturbed operating modes delivered by the updated model are important for improving the reliability of operational control systems and parametric estimation for data control mode states.

Fuel calorific value control process analysis and research based on IGCC power plant

AbstractThe stability of the equipment has been more and more important with the continuous development of IGCC (Integrated Gasification Combined Cycle) technology. The control of the calorific value of the fuel gas of the gas turbine is one of the most important factors for the stable operation of the gas turbine. There are many variables in the calorific value of IGCC fuels that will cause unstable fuel combustion conditions and low thermal efficiency. In terms of process equipment, process conditions, instrument control calculation, and logic adjustment, this paper studies the automatic adjustment system of the calorific value of syngas for IGCC gas turbine fuel. The calorific value of the syngas can be automatically adjusted under different working conditions of the gas turbine. It helps the stable combustion of the gas turbine to form a perfect, efficient, reliable calorific value control system.

Developing a Remote Access System by Interfacing ESP32 Microcontroller with 4X4 Keypad

Remote access with a microcontroller refers to the capability to control and communicate with a system based on a microcontroller from a remote location. The paper discusses the creation of a reliable remote access and control system using the ESP32 microcontroller and a 4x4 keypad. This system blends ease of use with robust security measures. With the increasing demand for secure access control solutions, this system makes a significant contribution to the realm of IoT-based authentication systems. Future endeavors may encompass scalability testing, integration with other biometric authentication methods, and additional refinements to expand its applicability

Evaluasi Lingkungan Pengendalian dengan Kerangka Pengendalian Internal COSO di KPP Pratama Jakarta Pesanggrahan

The control environment is crucial for establishing a reliable internal control system to prevent corporate fraud at the Jakarta Pesanggrahan Tax Office. It collects state revenue and accesses sensitive taxpayer information, including personal identity and financial data, making it susceptible to fraud risks. This study evaluates the control environment components of the Jakarta Pesanggrahan Tax Office using the 2013 edition of the COSO Internal Control Framework. The study used qualitative descriptive and case study methods. The population of this tax office consists of 93 employees. Primary data was collected through semi-structured interviews with 20 informants from various sections. Secondary data was collected through online sources, regulations, reports, and a literature review. The novelty in this study is that researchers used thematic analysis to produce 37 themes used as indicators in the suitability assessment of control environment components. The research results show that Jakarta Pesanggrahan Tax Office has 31 out of 37 indicators. In the "The organization demonstrates a commitment to integrity and ethical values" component, there are findings of working hours violations. In the component "The board of directors demonstrates independence from management and exercises oversight of the development and performance of internal control," there are repeated findings from the Supreme Audit Agency of the Republic of Indonesia, and the structure of the Internal Compliance Unit needs to operate independently. In the component "Management establishes, with board oversight, structures, reporting lines, and appropriate authorities and responsibilities in the pursuit of objectives," there are differences in perceptions between personnel of the Compliance Committee and inconsistencies in work positions. In the "The organization demonstrates a commitment to attract, develop, and retain competent individuals in alignment with objectives," the Jakarta Pesanggrahan Tax Office has fulfilled all indicators. Finally, in the component "The organization holds individuals accountable for their internal control responsibilities in the pursuit of objectives," the finding is the form of quality inequality resulting from employee performance ratings. Overall, the study aims to contribute to developing knowledge about the control environment in the tax office.

A resilient approach for simultaneous fault detection and control for a class of nonlinear systems

The simultaneous fault detection and control (SFDC) has emerged as a reliable scheme. However, what happens when the designed structure undergoes changes? Such variations have the potential to cause instability and misdiagnosis. This paper delves into a cutting-edge SFDC structure that surpasses conventional designs in terms of reliability. The proposed Resilient Simultaneous Fault Detection and Control (RSFDC) structure considers variations in the designed parameters and provides a more robust and fault-tolerant approach to SFDC, with important implications for the design of reliable and resilient control systems in a broad range of applications. This scheme is formulated as a multi-objective optimisation problem, encompassing control and diagnosis objectives. Specifically, it aims to minimise the impact of faults and disturbances on the controlled output while reducing residual sensitivity to all changes and maximising the fault effects on the residual. Through simulation comparisons, this paper showcases the merits of the RSFDC structure in two examples, highlighting its superiority over other designs.

Impact of Internal Control Systems on Minimizing Fraud: The Case of Lebanon

Establishing reliable internal control systems in Lebanon is a challenge for businesses looking to reduce their vulnerability to fraud. The purpose of this research was to determine whether or not internal control measures were successful in reducing fraud in Lebanon’s commercial sector. The study polls 308 businesses to learn more about control methods such as division of responsibilities, audit frequency, and ethics education. The results illuminate the present status of internal controls in Lebanon, illuminating the country’s successes and failures in its efforts to prevent fraud. With the information from this research, businesses may improve their fraud prevention tactics and safeguard their assets in the Lebanese market. Keywords: Internal Control, Monitoring, Controlling Activities, Controlling Environment, Information & Communication

Modified Differential Evolution Algorithm for Governing Virtual Inertia of an Isolated Microgrid Integrating Electric Vehicles

In modern power systems, there is a greater penetration of renewable sources, resulting in the expansion of microgrid. By implementing RES instead of conventional synchronous machines, the system’s overall inertia is significantly reduced. Modern and future power systems must reduce system inertia and keep the frequency at its nominal value since frequency oscillation impacts on the functionality, stability, and resilience of the system. Therefore, creating a stable, scalable, and reliable virtual inertia control system is crucial to effectively minimize the deviations during significant contingencies. Consequently, taking into account the probable issues, the foremost objective of this research work is to improve the dynamic security of an island microgrid through the implementation of a frequency control concept based on virtual inertia control. In the research study, the proposed microgrid system comprises of photovoltaics, wind-generating units, thermal power units, storage units, electric vehicles (EVs), and loads. A cascaded PIDFN controller is optimally designed using a novel metaheuristic modified differential evolution (MDE) algorithm that regulates the frequency based on virtual inertia control. In the MATLAB®/SIMULINK environment, various operating situations such as load variations, RES, and EVs disconnection are investigated, and the performance of the VIC-based MDE controller was compared to that of other controllers based on evolutionary optimization algorithms such as DE and TLBO. The results validate that the recommended virtual inertia control strategy enhances the reliability of the system.

Design and experiment of a binocular vision-based canopy volume extraction system for precision pesticide application by UAVs

When unmanned aerial vehicles (UAVs) are used for orchard chemicals application, accurate measurement of the canopy volume can provide decision support for determining pesticide dosages, flight parameters, and droplet sizes. Using binocular camera ranging, this study presents a novel canopy segmentation algorithm that preprocesses light detection ranging data to extract sub-grid canopy volumes. A binocular vision-based canopy volume extraction system for UAV chemical application was developed. The system utilizes multi-degree-of-freedom adaptive balance technology to ensure that the binocular camera can still vertically detect the canopy even when the flight attitude changes. Performance experiments were conducted using artificial fruit trees with different leaf densities and regular cardboard box as measurement targets. The canopy volume measurements indicate that the new model accurately detects target contours. When flying at 2 m/s, the maximum errors between system-measured and actual volumes were 6.58 and 9.37 % for the rectangular and triangular, respectively. Increasing speeds and attitudes lead to increased errors and measurement variations. However, the position of the system relative to the target does not cause significant differences in results. The maximum measurement errors between system-measured and actual LiDAR values were 6.44 and 9.17 % for high- and low-density canopies, respectively. These results demonstrate that the proposed system has high measurement accuracy and provides a reliable precision UAV pesticide-spraying control system for plant protection based on real-time canopy detection.

Uncertainty and Sensitivity Study on Lateral Jet Interaction for Hypersonic Missile

The demanding working environment of hypersonic missiles imposes high requirements on the reliability and stability of the reaction control system. This work aims to investigate the impact of uncertainties in freestream and jet parameters on the flowfield and aerodynamic performance of a missile with a lateral jet. Initially, the influence of angle of attack and Mach number on aerodynamic characteristics is evaluated. The findings indicate that the lateral jet control effect is enhanced as the Mach number increases. Moreover, the interference force/moment does not vary linearly with the angle of attack, and there are notable differences in the flow characteristics when the jet is on the windward and leeward sides. Subsequently, six parameters are selected as input variables. The uncertainties of the output results are analyzed using a stochastic expansion based on the nonintrusive polynomial chaos method. Sensitivity analysis is performed using Sobol indices to estimate the relative contributions of each parameter to the overall uncertainty. Within the given uncertainty interval, the surface pressure of the missile exhibits significant variation, with a maximum uncertainty of approximately 480%. The uncertainty of the recirculation zone range is 50.14%, while the pitch moment amplification factor has an uncertainty of 52.44%. The freestream Mach number, angle of attack, and jet pressure ratio are identified as key factors affecting the aerodynamic performance, surface pressure coefficient, and jet penetration height. Conversely, the contribution of other parameters can be considered negligible.