Automatic Control Research Articles

Detection of Defects in Polyethylene and Polyamide Flat Panels Using Airborne Ultrasound-Traditional and Machine Learning Approach

This paper presents the use of noncontact ultrasound for the nondestructive detection of defects in two plastic plates made of polyamide (PA6) and polyethylene (PE). The aim of the study was to: (1) assess the presence of defects as well as their size, type, and orientation based on the amplitudes of Lamb ultrasonic waves measured in plates made of polyamide (PA6) and polyethylene (PE) due to their homogeneous internal structure, which mainly determined the selection of such model materials for testing; and (2) verify the possibilities of building automatic quality control and defect detection systems based on ML based on the results of the above-mentioned studies within the Industry 4.0/5.0 paradigm. Tests were conducted on plates with generated synthetic defects resembling defects found in real materials such as delamination and cracking at the edge of the plate and a crack (discontinuity) in the center of the plate. Defect sizes ranged from 1 mm to 15 mm. Probes at 30 kHz were used to excite Lamb waves in the slab material. This method is sensitive to the slightest changes in material integrity. A significant decrease in signal amplitude was observed, even for defects of a few millimeters in length. In addition to traditional methods, machine learning (ML) was used for the analysis, allowing an initial assessment of the method’s potential for building cyber-physical systems and digital twins. By training ML models on ultrasonic data, algorithms can distinguish subtle differences between signals reflected from normal and defective areas of the material. Defect types such as voids, cracks, or weak bonds often produce distinct acoustic signatures, which ML models can learn to recognize with high accuracy. Using techniques like feature extraction, ML can process these high-dimensional ultrasonic datasets, identifying patterns that human inspectors might overlook. Furthermore, ML models are adaptable, allowing the same trained algorithms to work on various material batches or panel types with minimal retraining. This combination of automation and precision significantly enhances the reliability and efficiency of quality control in industrial manufacturing settings. The achieved accuracy results, 0.9431 in classification and 0.9721 in prediction, are comparable to or better than the AI-based quality control results in other noninvasive methods of flat surface defect detection, and in the presented ultrasonic method, they are the first described in this way. This approach demonstrates the novelty and contribution of artificial intelligence (AI) methods and tools, significantly extending and automating existing applications of traditional methods. The susceptibility to augmentation by AI/ML may represent an important new property of traditional methods crucial to assessing their suitability for future Industry 4.0/5.0 applications.

Control system and process optimization for electroless nickel plating

A novel method based on mid-frequency vibration is proposed to eliminate coating defects such as bubbles during electroless nickel plating. An automated control system for the plating, enabling precise and stable measurements and adjustments of critical parameters such as plating solution temperature, pH, and nickel ion concentration, is also established, which significantly improves process efficiency and coating quality. Experimental results indicate that the system is capable of realizing stable operation over extended periods. A nonporous nickel–phosphorus coating with a thickness greater than 200 μm is successfully obtained, with high phosphorus content, robust adhesion, and superior machinability.

Innovative Solar Water Pump with Automatic Water Level Regulator for Efficiency Rice Field Irrigation

Nowadays, most of human activities are related to the use of technology. The invention of various innovative ideas that simplify human life is essential. One of the uses advancement technologies can applied in agricultural field, especially for irrigation processes since it becomes the critical step in agricultural activity since it ensures that plants receive an adequate water. Due to the importance of irrigation, this community service activity aimed to provide information on how to build a solar pump for irrigation purposes and implement an innovative solar water pump with automatic water level control to improve the efficiency of irrigation of rice fields in Bekiung Village. The system is designed using solar panels as the main energy source, minimizing dependence on conventional electricity and fossil fuels. With the integration of water level sensor and automatic control system, the pump is able to adjust the water supply in real-time based on the actual needs of rice plants. Field tests show that the system is able to provide water consistently and efficiently, reducing water and energy wastage. The implementation of this technology not only improves irrigation efficiency, but also supports environmentally friendly sustainable agriculture. The results of this study are expected to serve as a model for other villages facing similar challenges in irrigation water management.

Fire Fighter Robot Using IOT and Mobile Application

In today's fast-paced world, fire hazards pose significant risks to life, property, and the environment. Traditional fire detection systems often rely on human intervention, leading to delays in response time and exacerbating the damage caused by fire incidents. Our project, the IoT-Based Automatic Fire Detection and Extinguisher Robot, addresses this challenge by utilizing a combination of modern sensor technology, robotics, and IoT to provide an autonomous and real-time solution. The robot is equipped with flame and temperature sensors that allow it to detect fires at an early stage. Once a fire is detected, the robot activates its movement mechanism using DC motors to navigate toward the fire while the integrated servo-controlled water pump precisely sprays water to extinguish the fire. In addition to automatic firefighting, the robot features obstacle detection using ultrasonic sensors, ensuring safe navigation in complex environments. The system includes Bluetooth and Wi-Fi communication, allowing for remote control via an Android mobile app. This app provides both manual and automatic control options and sends real-time fire alerts when the robot detects a fire. This autonomous system minimizes human intervention, speeds up response times, and reduces fire damage effectively. The robot is powered by an ESP32 microcontroller, which processes data from the sensors and controls the motors and water pump. The rescue pod feature allows the robot to perform additional operations like transporting sensitive materials during emergencies. The system's IoT functionality enables real-time alerts and remote monitoring, enhancing its capability as a scalable and cost-effective solution for residential, commercial, and industrial fire safety.

Application and optimisation of intelligent control system for home robots

Abstract. As a significant part of the smart home, intelligent home robots can provide a variety of convenient home services such as automatic cleaning, elderly care, entertainment interaction, etc., which are highly valued and favoured by the majority of home users, and the market scale is expanding. However, the design and optimization of the control system represents a crucial technical challenge to truly realize the intelligence and autonomy of home robots. This paper presents a comprehensive analysis of the design and optimization of automatic control systems for intelligent home robots, which aims to improve the performance and user experience of intelligent home robots and better meet the needs of families. Through collection and analysis of the research on domestic robots and their control technology ,the core technical elements of the control system are summarized and refined, and the hardware structure and software framework of the control system are analyzed. The research results provide valuable insights for improving the performance and capabilities of home robot control systems to better meet the diverse needs and expectations of home users. These innovations provide a solid foundation for advancing the development of intelligent robots in the home. Future trends in control systems may include enhanced perceptual capabilities and decision-making intelligence to enable robots to better understand and meet the needs of home users.

Smartphone microscopy: Design and implementation of a dual magnification system

This paper presents a dual magnification smartphone microscope designed for versatile imaging, enabling low magnification for wide-field viewing and high magnification for detailed biological sample analysis and automatic control of the working distance. It offers a cost-effective alternative to traditional lab microscopes, particularly in low-resource settings. Simulated, optimized, and designed using Ansys Zemax OpticStudio, the microscope was fabricated with 3D printing technology. Dual magnification (150x and 1000x) was achieved with two optical paths, improving resolution to 1 µm at higher and 1.5 µm at lower magnifications. The design provides clear and accurate images. The smartphone integration enhances usability, allowing easy magnification switching, image capture, and potential use of diagnostic applications.

Electromyographic analysis of upper limb muscles for automatic wheelchair propulsion control

Electromyographic analysis of upper limb muscles for automatic wheelchair propulsion control

Afpdb - an efficient structure manipulation package for AI protein design.

The advent of AlphaFold and other protein Artificial Intelligence (AI) models has transformed protein design, necessitating efficient handling of large-scale data and complex workflows. Using existing programming packages that predate recent AI advancements often leads to inefficiencies in human coding and slow code execution. To address this gap, we developed the Afpdb package. Afpdb, built on AlphaFold's NumPy architecture, offers a high-performance core. It uses RFDiffusion's contig syntax to streamline residue and atom selection, making coding simpler and more readable. Integrating PyMOL's visualization capabilities, Afpdb allows automatic visual quality control. With over 180 methods commonly used in protein AI design, which are otherwise hard to find, Afpdb enhances productivity in structural biology by supporting the development of concise, high-performance code. Code and documentation are available on GitHub (https://github.com/data2code/afpdb) and PyPI (https://pypi.org/project/afpdb). An interactive tutorial is accessible through Google Colab. Supplementary data are available at Bioinformatics online.

Advanced Sliding Mode Design for Optimal Automatic Generation Control in Multi-Area Multi-Source Power System Considering HVDC Link

The multi-area multi-source power system (MAMSPS), which uses a variety of power sources including gas, hydro, thermal, and renewable energy, has recently been implemented to balance the growing demand for electricity and the overall capacity for power generation. In this paper, an integral sliding mode control with a single-phase technique (ISMCSP) is applied to two areas, with each area including gas–wind–thermal power systems with HVDC system. Firstly, a two-area gas–wind–thermal power system with HVDC (TAGWTPSH) is the first model in this scheme to consider the parameter uncertainties of a MAMSPS. Secondly, sliding mode design law with a single-phase technique is introduced to alleviate chattering and oscillation problems. Then, power system stability is ensured by the Lyapunov control theory based on the new LMIs technique. Thirdly, the ISMCSP’s effectiveness in a MAMSPS is also assessed under random load patterns and parameter variations regarding settling time and over-/undershoot. The ISMCSP was created to alter the fundamental sliding mode control, and therefore the suggested approach performs better than recently published approaches. This is demonstrated by the frequency overshoot deviation value in frequency deviations: 0.7 × 10−3 to 2.8 × 10−3 for the TAGWTPSH with the suggested ISMCSP. In the last case, for random changes in load from −0.4 to +0.5 p. u, the proposed ISMCSP method still stabilizes the frequency of the areas meeting the standard requirements for AGC.

THE SOFTWARE IMPLEMENTATION FOR AUTOMATIC GENERATION OF PETRI NETS

Context. The important task was solved during this scientific research related to specific development and verification of thefundamental suitability of the software application that provides visualization of the automatic synthesis of Petri nets while setting upthe multi-level control systems. This task is current because the for the first time the integration of means of discrete-continuous networksfrom the DC-Net environment in the Labview environment is realized through the implementation of automatic synthesis ofPetri nets. This makes it possible to automate the processes of synthesis for the control algorithms based on the development of appropriateintelligent systems. Objective. The purpose of the scientific work is to minimize the time and to automatize process in synthesis of the control algorithmsby integrating the means of discrete-continuous networks and implementing the principles of automatic synthesis of Petri nets. Method. This scientific article proposes the principle for automatic formation of Petri nets based on logical algorithm for classifyingvarious uncorrected algorithms. The multilayer neural network in the Labview 2009 software environment was implemented torealize the appropriate algorithm. This artificial neural network provides algorithm formation, automatic synthesis and operation ofPetri nets. The article is devoted to the study of operating principle of the software application implementing such automatic synthesisof Petri nets while setting up the multi-level control systems. Results. A number of experiments were performed on the classification of algorithms and formation of Petri nets based on theready-made software application. The control system was automatically set up based on the Labview 2009 environment applicationfor the determined object. As a result of these experiments we have determined the fundamental suitability of the software application for the synthesis ofsome multi-level automatic control systems. It was also shown during these experiments that all mismatch signals in the system anddeviations from the ratios of values controlled variables are reduced to zero. All parameters of the control systems settings werenoted after the multi-level system setting procedure on the front panel of the virtual stand. Conclusions. The task related to the software application development based on the Labview 2009 environment which providesthe automatic synthesis of Petri nets was solved in this scientific work. Thus the method of automatic synthesis of Petri nets andtechnology for developing certain algorithms based on the functioning of the artificial neural network was further developed.

DEVELOPMENT OF AUTOMATED CONTROL SYSTEM AND REGISTRATION OF METAL IN CONTINUOUS CASTING

Context. Modern industrial enterprises face challenges that require introduction of latest technologies to improve efficiency and competitiveness. In metallurgy, one of key stages is continuous casting, where quality of products and economic performance of enterprise depend on accuracy and efficiency of process control. Products made using continuous casting technology are widely used in various industries due to their high mechanical properties, structural uniformity and cost-effectiveness. The development of automated metal management and registration system is becoming not only relevant, but also necessary to ensure stable and efficient production. The problem of improving quality of metal products has always been one of most important tasks in steel industry. Imperfect technological processes, human error and equipment malfunctions can lead to defects in finished metal products. This, in turn, affects final characteristics of products, their durability and reliability. To date, available sources have not yet found complete solution to this problem. Therefore, it is necessary to formulate problem and develop algorithm for operation of automated system for controlling and registering metal in continuous casting. Objective. The goal of work is to develop automated metal management and registration system to improve quality of metal products. Method. To achieve this goal, parametric model was proposed, which is formalized on basis of set theory. The model takes into account key parameters of continuous casting process: material characteristics, structural features of crystallizer, casting modes, metal level in crystallizer, and position of shot stopper. Results. The problem was formulated and key parameters were determined, which are taken into account in system’s algorithm, which made it possible to develop system for controlling parameters of continuous casting to solve problem of improving quality of metal products. Conclusions. To improve quality of metal products and stability of casting process, parametric model was created that is comprehensive, allows optimization of key parameters and ensures accuracy of process control by integrating not only modes of product formation, but also takes into account specific properties of source material (chemical composition of material grade, etc.) and design features of casting plant. Algorithm for automated control system has been developed that takes into account relationships between certain key parameters and ensures optimal control of casting process. Based on proposed complex parametric model and algorithm, automated control and metal registration system was created. The focus of work is on quality and efficiency of metal management and registration in continuous casting, based on modern methods of computer science and engineering. A comprehensive experimental comparison of developed system with commercial analogs in real production conditions was carried out, which allowed us to objectively assess its efficiency and reliability.

A study of automatic output power control methods for stand-alone photovoltaic power generation systems

Abstract The conventional power generation system’s output power automatic control structure is generally unidirectional, and the control coverage is small, leading to the increase in the random error obtained in the final test. Therefore, the design and research of this article are proposed. According to the current control demand, the generation system shall be stabilized first, and the power compensation shall be calculated. The multi-step mode shall be adopted to improve the control coverage and design the multi-step automatic control structure. According to this, it is constructed, and the automatic control processing is realized using jump balance. The test results show that compared with the traditional DFIG-DRWT system power output automatic control method and the traditional three-phase asynchronous generation system power output automatic control method, the random error finally obtained by the designed independent photovoltaic power station output power automatic control method is relatively effective. This indicates that the application effect and coverage of the designed power automatic control method are high, that controllability has been significantly improved, and that control flexibility has also been strengthened.

Multi-objective design of fractional frequency-load control for hydro-thermal system considering nonlinear models and uncertainty

One of the crucial quantities in the power system problem is frequency, which should never exceed its nominal value. In normal conditions of load changes, the frequency is adjusted by automatic generation control. Still, in the face of special conditions, such as logging of the downstream network from the main network or a significant amount of generated power leaving the circuit, the power imbalance between generation and consumption causes a rapid frequency drop. In this case, the automatic generation control cannot stop the frequency drop, so the frequency tends toward instability. In this paper, to automatically produce a water-thermal system in two zones of discrete and continuous modes, the design of a fractional controller is discussed and investigated in different functional conditions and uncertainties. The proposed NSGA-II multi-objective method is used in this article to optimize each area’s load frequency control parameters for various goals. The ideal response for the entire network will be obtained by modifying these responses using a multi-factor method. This paper defines a multi-zone frequency load control based on time objective functions and eigenvalues. Based on the speed changes for the proposed algorithm and the novel approachfunction method employed in the control design. The simulation performed and analyzed in different working conditions with different comparative criteria has been discussed and investigated. Compared to more contemporary techniques, the simulation results show that the system’s performance is guaranteed. The main successes of the suggested method in comparison to earlier methods have been the reduction of overshoot, undershoot, and settling time.

Automatic control algorithm for V2G frequency response mode of electric vehicle charging station

Abstract To solve the problem of excessive fluctuation of the V2G load of the electric vehicle charging pile, this paper proposes an automatic control algorithm for the V2G frequency response mode of the electric vehicle charging pile. The FPGA is used as the core processing unit to collect and process the V2G frequency data of the charging pile; the multiple linear regression model is used to predict the charging and discharging loads, and the automated two-layer control model is established; the sparrow search algorithm is used to optimize the weights and thresholds of the BP neural network to realize the control of the V2G frequency response mode. The experimental results show that the load prediction error of this method is small. After the automatic control, the load fluctuation of the charging pile is small, and the electric vehicle charging pile’s V2G frequency response control effect is better.

A Neural-Metaheuristic Kalman Filter for Moving Microburst Wind Shear Identification

Microburst wind shears (MB) are powerful localized three dimensional (3D) columns of wind that occur when cooled air drops from the base of thunderstorms at high speeds. They eventually hit the ground and spread out in all directions. As such MBs are considered a major atmospheric hazard for aircrafts (ACs), especially in terminal flight phases. Though pilots train regularly to survive it, yet the most recommended practice within the aviation community is to avoid its encounter upon detection. Some modern aircrafts have predictive wind shear warning systems, but they have limited short range capability and do not provide quantitative data for engineering application. In this sense, accurate onboard detection and identification of MBs and its characteristics is of importance for flight safety, whose success can lead to design of automatic flight control systems (FCSs) that reduce the risk of aircraft crash landings and accidents. Even though there are some studies on FCS designs for MB encounter, research on MB identification is rare but ongoing. To this aim, the present study is among the firsts that focuses on online identification of multiple and moving MB parameters using onboard aircraft air data and inertial sensors. The identification task is initially performed using the aircraft six degrees of freedom (6DoF) equations of motion (EOM) integrated with a 3D MB model via the utility of nonlinear Kalman filtering (KF) algorithms. Subsequently, an enhanced neural metaheuristic Kalman filter (NMKF) is proposed that improves the estimation accuracy of the MB model parameters. The results demonstrate the efficacy of the proposed NMKF in comparison with previous studies.

Assessing jamming and spoofing impacts on GNSS receivers: Automatic gain control (AGC)

Assessing jamming and spoofing impacts on GNSS receivers: Automatic gain control (AGC)

Flexible heat and power load control of subcritical heating units based on energy demand-supply balance

To fulfill the requirement for enhancing the flexibility of heating units within the framework of renewable energy grid integration. In this study, a proposed optimal control strategy for heating units borrows the heat extraction output to perform rapid load changes; the boiler heat supply within the unit is clearly differentiated from the turbine energy demand, and formulate corresponding control signals. The coordinated control of the boiler and turbine based on the energy demand-supply balance of the unit as secondary control for the final load accuracy, ensuring its safe and stable operation. To further enhance the control performance, an improved sparrow optimization algorithm with butterfly search is designed to adjust the controller parameters. Finally, field tests on a 300MW subcritical heating unit reveal that the automatic generation control performance index is improved by 32.16% compared to the traditional coordinated control strategy, while taking less impact on the heat user. These results validate the exceptional performance and significant practical value of the optimized control strategy.

Equipment control algorithm for cooling plant based on graph theory and path planning

This paper presents a novel path planning-based start-stop control algorithm for equipment in cooling plants designed to address the limitations of traditional serial start-stop control logic. The algorithm employs graph theory and path planning techniques to abstract the cooling plant schematic into a directed graph, enabling the selection of appropriate control paths and facilitating effective start-stop control decisions for the equipment. A key feature is the dynamic updating of the graph after each operation, which enables adaptive control target adjustments and prevents control blocking issues. Validation with real case scenarios demonstrates the effectiveness of the algorithm in automatic start-stop control, identifying equipment deviations, and handling faulty equipment switching. The algorithm also has the ability to handle some incorrectly turned on equipment, shutting down redundant equipment in the cooling plant system that is not in efficient operation. This algorithm shows the potential as an underlying execution algorithm of an advanced optimization algorithm to accelerate the implementation of advanced optimization algorithms.

Chinese Patent Review of Integrated Management System for Agricultural Machinery

Background: With the rapid development of China's economy and the accelerating process of agricultural mechanization, agricultural machinery has become increasingly popular in agricultural production activities. At the same time, problems in agricultural machinery management have gradually been exposed, hindering the development of modern agriculture. Objective: This study aimed to discuss the development trend of agricultural management and modern agriculture by analyzing and discussing the related patents of agricultural machinery management systems. Methods: The development of agricultural machinery management was summarized, and the representative patents related to agricultural machinery management systems, agricultural machinery automatic control systems, and agricultural machinery terminals were analyzed. Results: By analyzing the existing patents of the agricultural machinery management system, the paper summarized their applications in agricultural management and obtained their future development trend. Conclusion: In agricultural machinery management, we should actively adopt complementary strategies to solve various problems and improve the management level of agricultural machinery. The continuous improvement of the agricultural machinery management system is of great significance to the automation of agricultural production and the modernization of agricultural management in China.

DEVELOPMENT OF A MECHATRONIC SYSTEM FOR A SILKWORM INCUBATOR

In this study, the effectiveness of using a mechatronic system in the incubation of silkworm eggs was studied. The incubator consists of an SCD41 sensor, an ESP32 microcontroller, a TES1-12706 air cooler, an electric heater and a ventilation systembo'lib, harorat, namlik va CO2, which provides automatic control of temperature, humidity and CO2 quantity2. The study showed that when using the new system, the level of egg viability increased by 4.1%, and the yield of cocoons-by 5.8%. However, the overall length of the silk fiber and the continuous length have also been improved. This innovative system can be of great importance for improving product quality and ensuring economic efficiency in the silk industry.