Operation Of Control System Research Articles

PEMFC Gas-Feeding Control: Critical Insights and Review

Proton exchange membrane fuel cells (PEMFCs) are currently a relatively mature type of hydrogen energy device due to their high efficiency and low noise compared to traditional power devices. However, there are still challenges that hinder the large-scale application of PEMFCs. One key challenge lies in the gas supply system, which is a complex, coupled nonlinear system. Therefore, an effective control strategy is essential for the efficient and stable operation of the gas control system. This paper aims to provide a comprehensive and systematic overview of the control strategies for PEMFC anode and cathode supply systems based on an analysis of 182 papers. The review covers modern control theories and optimization algorithms, including their design, objectives, performance, applications, and so on. Additionally, the advantages and disadvantages of these control methods are thoroughly evaluated and summarized.

Recent Advances in controlled manipulation of micro/nano particles: A review

Abstract This review discusses the transformative impact of micro/nano particle manipulation techniques across scientific and technological disciplines. Emphasizing the pivotal role of precise control at the micro and nanoscale, the paper categorizes manipulation strategies into mechanical/surface force-based, field-control manipulation, and microfluidics manipulation. It addresses challenges specific to the submicrometer scale, highlighting the strengths and limitations of each approach. The unique behaviors exhibited by objects at the micro–nano scale influence the design and operation of manipulators, algorithms, and control systems, particularly in interactions with biological systems. The review covers dielectrophoresis and magnetic manipulation, showcasing their applications in particle manipulation and microfluidics. The evolution of optical tweezers, including holographic, surface plasmon-based, and optical fiber tweezers, is discussed, emphasizing their contributions in various scientific fields. Additionally, the paper also explores the manipulation of micro/nano particle in microfluidic platforms. The comprehensive review underscores the significance of understanding manipulation strategies in diverse environments, anticipating further advancements in science and technology.

Investigation of control system operation in plug-in four-wheel drive of wheeled vehicles on roller test benches

Investigation of control system operation in plug-in four-wheel drive of wheeled vehicles on roller test benches

Organizing the automated system of dispatch control over pump units at water pumping stations

The design and operation of modern dispatch control systems for pumping units involves comprehensive solution to separate engineering, technical, and scientific problems. The object of research is information processes enabling the operational modes of electrically driven pumping units at water pumping stations. This paper solves the scientific and technical task related to developing topology, hardware, and software tools, control algorithms, dispatch interface, and researching the modes of operation of pumping units in dispatch control systems at water pumping stations. Algorithms for controlling pumping units have been implemented, the advantage of which is the possibility of automated calculation of parameters for technological PID-controllers, taking into account the current electrical parameters of the frequency-controlled electric drive of pumping units and operating conditions. The WEB-oriented dispatch interface of the SCADA-based pumping unit control system was designed and tested, which enables control process in real time. Features of the developed dispatch control system are improved topology, expanded functionality, energy-saving control modes, and the possibility of further modernization based on the principles of standardization and unification of hardware and software tools and design procedures. The developed dispatch control system for pumping units at water pumping stations has been implemented and is successfully operated at an industrial water supply enterprise. The results provided for an increase in technical and economic indicators during the operation of technological equipment due to the efficiency of control and management procedures, energy-saving operational modes of the frequency-controlled electric drive of pumping units.

Automation of the Oil Extraction Process Performed by Means of A Screw Press

Abstract The continuous development of the oil-manufacturing industries causes the necessity of improving extraction technologies. In this case, the specific interest is focused on the control systems of screw presses. Among a great variety of such machines, the small household presses are in significant demand among consumers. Various seeds and kernels require different technological conditions to be provided in order to maximize the qualitative and quantitative characteristics of the extracted oil. Therefore, the main objective of this research is developing and testing the control system allowing for automation of the oil extraction process. Particularly, the temperature parameters of the pressing chamber, extracted oil, and electric motor are to be monitored and limited. In addition, the consumer should be able to predefine the mass of the oil to be extracted. Considering the small household screw press LiangTai LTP200, the general algorithm (block diagram) of the control system operation is proposed and the corresponding experimental prototype is developed. The latter is based on the Arduino Mega microcontroller and is equipped with three temperature sensors, two coolers (fans), one heater, and one mass sensor. The proposed control system allows for continuous monitoring and limiting of the pressing chamber, oil, and electric motor temperatures, as well as the mass of the extracted oil. The experimental data show that the pressing chamber preheating process lasts for about 3 min (170…190 s) and its maximal temperature does not exceed 44°C. The temperature of the extracted oil does not rise over 61°C. The motor temperature changes within the range of 69...71°C. The oil extraction productivity is as follows: 1.2 kg/h (sunflower seeds), 1.06 kg/h (walnut kernels), 0.9 kg/h (almond kernels), and 0.78 kg/h (peanut kernels). The obtained results can used in further investigations focused on analyzing the influence of these parameters on the quantitative and qualitative characteristics of the extracted oil.

System Integration Design of High-Performance Piezo-Actuated Fast-Steering Mirror for Laser Beam Steering System

This paper presents an innovative piezo-actuated fast-steering mirror (FSM) that integrates control design and system operation to improve the tracking performance of laser beam steering (LBS) systems. The proposed piezoelectric FSM is centered on two pairs of stacked actuators functioning in the tip-tilt direction via novel flexible hinges with strain-gauge sensors for position measurement. The suggested flexible hinge scheme allows the first fundamental resonance mode with the optical mirror to exceed 400 Hz while achieving an actuation range of ±5 mrad. Thus, the design offers a wider mechanical actuation range than conventional piezoelectric FSMs. Moreover, LBS systems that use fast-steering motion controllers should be robust against dynamic disturbances, such as periodic external vibrations. Such disturbances, inherently associated with the operating conditions for LBS systems, typically reduce the stability of the tip-tilt motion. To attenuate the effects of such disturbances, a high-precision control system is necessary for the tip-tilt motion. Therefore, a control method integrating a proportional–integral controller with an adaptive feedforward control (AFC) algorithm is outlined to enhance tip-tilt tracking performance during high-speed scanning, compared with conventional LBS systems. Based on experimental findings, the AFC algorithm boosted control performance under dynamic disturbances, such as sinusoidal vibrations with multiple frequencies.

Numerical analysis of the subway tunnel thermal environment to predict the train-mounted condenser inlet temperature in the cold climate zone of China

Reasonable control of the subway tunnel thermal environment is the main objective of the ventilation system design, which is critical to the effectiveness of the train-mounted condenser. In this study, a numerical model utilizing the dynamic mesh technique is developed to investigate the subway tunnel thermal environmental characteristics in the cold climate zone of China. Full-scale field measurements are implemented to verify the model’s accuracy. According to the simulation results, the single Piston wind shaft (PWS) (outlet end) is the optimal ventilation system in the cold climate zone of China. The effects of tunnel wall temperature, passenger flow, and regeneration braking system (RBS) efficiency on the subway tunnel thermal environment are thoroughly analyzed, which shows that the tunnel wall temperature has the greatest effect on the air temperature rise of the subway interval tunnel, the passenger flow has the greatest effect on the air temperature rise of the subway station tunnel. In contrast, the RBS efficiency has the least effect on the maximum condenser inlet temperature. On this basis, the predictive model for the maximum and average condenser inlet temperature is proposed. The findings of this study provide a theoretical basis for temperature control in subway tunnels in the cold climate zone of China and contribute to the safe and energy-efficient operation of subway environmental control systems.

Numerical Study on the Influence of the Slope Composition of the Asymmetric V-Shaped Tunnel on Smoke Spread in Tunnel Fire

Asymmetrical V-shaped tunnels often appear in tunnels crossing the river or urban underground road tunnels. The smoke flow inside is affected by a lot of factors. A full understanding of the smoke flow in this kind of tunnel is the basis of the smoke control. In this study, the effects of slope composition and fire heat release rate (HRR) on the longitudinal induced airflow velocity, the smoke back-layering length at the small slope side, and the maximum ceiling temperature were studied by the numerical method. The results show that when the fire occurs at the slope change point of the V-shaped tunnel, the maximum ceiling temperature decreases with the increase in the slope of the large-slope side tunnel. The longitudinally induced velocity is primarily related to the slope of the large-slope side tunnel and the fire HRR. When the slope difference between the side tunnels or the slope of the large-slope side tunnel is large, the smoke in the small-slope side tunnel flows back toward the fire source after reaching its maximum dispersion distance and then reaches a quasi-steady state. The smoke back-layering length is mainly affected by the slope and length of the large-slope side tunnel. When the slope of the large-slope side tunnel is 9%, the induced airflow velocity from the small-slope side can prevent the spread of smoke. The empirical models of the smoke back-layering length and the longitudinal induced airflow velocity in the small-slope side tunnel are drawn, respectively, by the theoretical analysis and the numerical results. This study can provide technical support for the design and operation of smoke control systems in V-shaped tunnels.

Prospects of autonomous railway transport development

The implementation of unmanned train control systems offers a number of advantages, such as increasing the capacity of railway lines and traffi c volumes, reducing the ‘human factor’, as well as reducing operating costs. The paper considers the challenges arising from the use of automatic train control systems, and presents the prospects for the implementation of automatic technologies in railway transport for various railway systems. The social and economic aspects of changing professional activities in railway transport are described. Grades of automation applicable to surface urban railwaytransport are presented. The issues of proving the functional safety of machine vision systems as part of the train traffic control system and determining their level of safety completeness are discussed. Examples of railway transport automation in Russia and other countries are given. Basic scenarios of automatic control system operation describing normal and abnormal situations are formulated. In conclusion, the levels of technological readiness of the reviewed solutions in the fi eld of train traffic automation are defi ned. The tasks faced by railway companies in implementing these technologies are outlined, and possible ways of overcoming obstacles to the introduction of automatic systems are proposed, taking into account the current political situation.

Anomaly Detection Method for Industrial Control System Operation Data Based on Time-Frequency Fusion Feature Attention Encoding.

Anomaly detection in industrial control system (ICS) data is one of the key technologies for ensuring the security monitoring of ICSs. ICS data are characterized as complex, multi-dimensional, and long-sequence time-series data that embody ICS business logic. Due to its complex and varying periodic characteristics, as well as the presence of long-distance and misaligned temporal associations among features, current anomaly detection methods in ICS are insufficient for feature extraction. This paper proposes an anomaly detection method named TFANet, based on time-frequency fusion feature attention encoding. Considering that periodic variations are more concentrated in the frequency domain, this method first transforms the time-domain data into the frequency domain, obtaining both amplitude and phase data. Then, these data, together with the original time-series data, are used to extract features from two perspectives: long-term temporal changes and long-distance associations. Finally, the six features learned from both the time and frequency domains are fused, and the feature weights are calculated using an attention mechanism to complete the anomaly classification. In multi-classification tasks on three ICS datasets, the proposed method outperforms three popular time-series models-iTransformer, Crossformer, and TimesNet-across five metrics: accuracy, precision, recall, F1 score, and AUC-ROC, with average improvements of approximately 19%, 37%, 31%, 35%, and 22%, respectively.

Energy analysis of a direct expansion heat pump assisted by a thermal photovoltaic panel for hot water production in several regions of Brazil

This study focused on evaluating the energy performance and economic viability of a direct expansion photovoltaic-Thermal Heat Pump (PV-T/HP) system for residential heating applications in various regions of Brazil. A detailed mathematical model was implemented to compare the PV-T/HP system with other solar heating technologies, as photovoltaic with solar evacuated tubes collector (PV+TSC) and photovoltaic with electrical heat water (PV+EHW), analyzing key metrics such as electrical efficiency, thermal efficiency, and levelized cost of heat (LCOH). The study revealed variations ranging from 7.5 to 2.5 in the Coefficient of Performance (COP) of the heat pump under different solar irradiation and ambient temperature conditions, emphasizing the necessity for future optimization to enhance the system performance. Results indicated that cities with the lower ambient temperature such as Belo Horizonte and Porto Alegre exhibited favorable conditions for the PV-T/HP system, leading to increased energy generation and positive net electricity production. The study highlighted the need for tailored strategies to control system operations, limit compressor consumption, and improve overall efficiency. These findings contribute to the understanding of PV-T/HP systems in residential heating applications, showcasing their potential for sustainable energy solutions in Brazil.

건설현장의 스마트 안전보건활동 요소에 관한 중요도 분석

The purpose of this study is to analyze the importance of smart safety and health activity elements in order to increase the execution power and effectiveness of smart safety and health activities at construction sites. To this end, in this study, the elements of smart safety and health activities were derived from the technical, educational, and management levels, and AHP(Analytic Hierarchy Process) survey data were collected and analyzed for safety-related experts at construction sites. As a result of the relative importance analysis of the elements of smart safety and health activities, the priority of smart experience education programs was the highest, and smart risk assessment system, smart safety control system operation, smart worker safety management, smart work site management, smart technology specialized training instructors, smart risk area access management, safety and health management system, smart education certification system, smart equipment management, and smart non-face-to-face education were sequentially high. The results of this analysis can be evaluated as the most effective way to prevent and act on safety accidents in construction sites and situations using Augmented Reality(AR) and VR(Virtual Reality), and it needs to be introduced first. In addition, in order to prevent and reduce various industrial accidents at construction sites, it suggests that smart safety and health activities at the enterprise level, such as smart experience education, risk assessment, and integrated safety management systems, are needed rather than smart safety and health activities at the individual level.

Optimal scheduling of smart home energy systems: A user-friendly and adaptive home intelligent agent with self-learning capability

This paper proposed a user-friendly and adaptive home intelligent agent with self-learning capability for optimal scheduling of smart home energy systems. The intelligent agent autonomously identifies model parameters based on system operation data, eliminating the need for manual input and making it more user-friendly and practical to implement. It can also self-learn the latest energy consumption information from an updated dataset and adaptively adjust model parameters to accommodate changing conditions. Utilizing these determined models as input, the intelligent agent performs day-ahead optimal scheduling using the proposed many-objective integer nonlinear optimization model and automatically controls system operation. Experimental studies were conducted on a laboratory-based smart home energy system to verify the effectiveness of the developed intelligent agent in different scenarios. The results consistently demonstrate Mean Absolute Percentage Errors below -12.7 % across all three scenarios, indicating the accuracy of the intelligent agent. Furthermore, the optimal scheduling significantly enhances system performances. After optimization, daily operational costs, peak-valley differences, and CO2 emissions were reduced by 34.1 % to 81.6 %, 29.2 % to 36.7 %, and 19.6 % to 43.2 %, respectively. Moreover, the PV generation self-consumption rate and self-sufficiency rate improved by 29.6 % to 38.0 % and 40.5 % to 49.4 %, respectively. The proposed intelligent agent provides invaluable guidance for optimal dispatch of smart home energy systems in real-world settings.

Asymptotical Mean-Square Stabilization of Networked Control Systems Operating Over Multipath Routing Networks

Asymptotical Mean-Square Stabilization of Networked Control Systems Operating Over Multipath Routing Networks

Perspectives on risk analysis and control for real-time operation of flood control systems

Flood control operation, a non-engineering measure, can efficiently manage flood disasters within a river basin. However, numerous uncertainties exit in the real-time operation of flood control systems, creating risks in decision-making. As an efficient tool to mitigate these risks, risk management has garnered increasing attention in real-time flood control operation. This communication offers a series of suggestions for future research concerning risk management in real-time flood control operation, including risk assessment, risk diagnosis, and risk control methods.

Aerodynamic optimization method of intake grille of active clearance control system for turbines based on modified social spider algorithm (MSSA)

During the operation of an active clearance control (ACC) system of a turbine, the aerodynamic performance of the intake grille indirectly influences its control. To improve the performance, an aerodynamic optimization method is proposed, consisting of parameterization, an optimization algorithm, and a fitness evaluation. During parameterization, its geometry is represented by seven geometric variables. A modified social spider algorithm is used as the optimization algorithm. To evaluate the aerodynamic performance of the grille, a special fitness function is adopted, obtained using an adaptive topological multi-layer feedforward artificial neural network. To verify the feasibility of this method, experiments and numerical calculations are carried out on the original and optimized intake grilles. The results show that the average intake flow rate and average total pressure recovery coefficient of the optimized grille have increased by 17.3% and 4.9%, respectively.

Memristor-based adaptive neuromorphic perception in unstructured environments

Efficient operation of control systems in robotics or autonomous driving targeting real-world navigation scenarios requires perception methods that allow them to understand and adapt to unstructured environments with good accuracy, adaptation, and generality, similar to humans. To address this need, we present a memristor-based differential neuromorphic computing, perceptual signal processing, and online adaptation method providing neuromorphic style adaptation to external sensory stimuli. The adaptation ability and generality of this method are confirmed in two application scenarios: object grasping and autonomous driving. In the former, a robot hand realizes safe and stable grasping through fast ( ~ 1 ms) adaptation based on the tactile object features with a single memristor. In the latter, decision-making information of 10 unstructured environments in autonomous driving is extracted with an accuracy of 94% with a 40×25 memristor array. By mimicking human low-level perception mechanisms, the electronic neuromorphic circuit-based method achieves real-time adaptation and high-level reactions to unstructured environments.

ICRH operations during the JET tritium and DTE2 campaigns

The JET-ILW pure tritium and deuterium–tritium (DTE2) experimental campaigns took place in 2021–2022. Tritium (T) and deuterium–tritium (D–T) operations present challenges not encountered in present day tokamaks (Horton et al 2016 Fusion Eng. Des. 109–111 925–36). This contribution focuses on ion cyclotron resonance heating (ICRH) operations in tritium and deuterium–tritium plasmas, starting with a summary of the program of improvements to the ICRH system which spanned a few years prior to these experiments. Procedures were implemented to address specific constraints from tritium and deuterium–tritium operations (tritium safety and reduced access to the RF generator area) and increase the system reliability and power availability during plasma pulses. Operation of the upgraded real time RF power control system that maximises the launched power while taking into account limitations from the system or antenna coupling is described. We also report on the result from dedicated pulses performed to assess the potential harmful impact of the 2nd harmonic tritium resonance in the plasma, close to the inner wall, when using the standard central hydrogen minority ICRH scheme. During DTE2, the ITER-like antenna was not used because water leaked from an in-vessel capacitor into the vessel on day-2 of the experimental campaign. The lessons learnt from this incident are highlighted. Finally, the ICRH plant adjustments required to safely perform ion cyclotron wall cleaning discharges are described.

Analysis of the operation of the microprocessor control system of a bridge crane using optimum control laws

This work presents the results of studies on the influence of the error of the main parameters of the bridge crane on the quality of optimal control. The quality of control refers to the exact positioning of the load at the stopping point and the magnitude of the final fluctuations of the load after the crane stops. The concept of optimal control is based on L.S. Pontryagin's maximum principle, which is when the goal is achieved by switching the acceleration-braking control of the load suspension point according to a specific algorithm. To achieve the maximum speed of operation of the crane, certain restrictions and conditions have been removed, namely, the refusal to eliminate load fluctuations during crane acceleration, which simplifies the subsequent elimination of load fluctuations during crane braking. However, this is an unnecessary waste of time, and therefore, acceleration is carried out at the maximum possible acceleration without eliminating load fluctuations. Of course, at the same time, significant fluctuations in the cargo occur, and they continue throughout the entire time the crane is moving. Moreover, the final goal is achieved only at the end of the cycle by switching the acceleration-deceleration modes - the cargo is delivered precisely to the specified point without fluctuations after the crane stops. A PC program that generates optimal control laws for a specific crane has been developed. This program can be used for any lifting machine where the suspension point moves in a straight line, and flexible load suspension is used, such as overhead or gantry cranes, hoists, etc. The results of the research were tested on several objects: a 0.5t crane, a 5t bridge grab crane, and models of bridge cranes. In each case, a good coincidence of theoretical and experimental results was observed, resulting in effective management of the object. The original microprocessor system implemented the optimal control laws, built first based on the MKP-1 microcontroller and then based on Arduino. However, a good result is guaranteed only if the fundamental parameters of the crane coincide with the theoretical ones. This is not easy to achieve during the actual operation of the crane. They vary within a specific range. The article examines how the error in each of the main parameters of the crane affects the result and how the control system can be improved to reduce the negative impact to a minimum. Keywords: optimal control, elimination of load fluctuations, accurate positioning, crane, microprocessor, reloading cycle

Total Energy-Based Control Design and Optimization for Lift-Plus-Cruise Aircraft

This paper presents a methodology for optimizing a Total Energy–based control system architecture for a lift-plus-cruise vertical takeoff and landing urban air mobility concept. The Total Energy Control System algorithm, which was originally developed for fixed-wing applications, is extended to also be applicable to hovering and transitioning flight. Control system parameters are optimized using a genetic algorithm optimization scheme, subject to constraints on dynamic stability and control response characteristics. Control system optimization and flight simulations are performed using the Modular Aircraft Dynamics and Control Algorithm Simulation Platform. Results presented include simulations of the optimized flight control system operation for maneuvering scenarios representative of hover, transition, and forward flight conditions as well as during transitions between vertical and forward flight modes. The presented results demonstrate the effectiveness of the proposed control system architecture and the demonstrated optimization methodology.