Automatic Control Mechanism Research Articles

This study addresses the problem of determining the existence and uniqueness of periodic solutions to a class of impulsive neutral dynamic equations that incorporate infinite delay, defined over a periodic time scale denoted by . The focal point of this work is a complex dynamic system that integrates multiple mathematical features: neutral terms, impulsive discontinuities at discrete instances, and an integral representation of the system’s historical behavior extending indefinitely into the past. The dynamic model under consideration involves a delta derivative, multiplicative operator terms, and delayed functional components, and is governed by impulsive effects at specified time points. The analysis is grounded in a general framework that accommodates both discrete and continuous behavior through the unifying language of time scale calculus. To establish the existence of periodic solutions, we utilize Krasnoselskii’s fixed point theorem—an essential tool in nonlinear operator theory known for its effectiveness in handling non-compact and non-linear mappings in Banach spaces. In contrast, the uniqueness of the solution is ensured by applying the Banach contraction principle, which demands more restrictive structural conditions on the system’s parameters but provides strong guarantees of solution distinctiveness. The theoretical contributions presented herein not only address the inherent analytical challenges posed by the neutral and impulsive dynamics but also offer valuable insights into systems exhibiting long-term memory. Such systems are prevalent in various scientific domains, including automatic control mechanisms with feedback delays, macroeconomic models driven by historical trends, and biological oscillators subject to abrupt environmental perturbations. By integrating advanced methods from time scale calculus, infinite-dimensional functional analysis, and fixed point theory, this work offers a comprehensive approach that enhances both the theoretical understanding and practical applicability of periodic solutions in delay-dominated dynamic systems.

Introduction: Motor skill acquisition is influenced by motivational and attentional factors. Among these, the focus of attention—internal or external—plays a critical role in performance and learning. This study examined the effects of different attentional foci on motor skill learning in adolescents. Methods: Seventy-seven adolescents (M = 16.5 years, SD = 1.4) of both sexes performed a Response Time task. After one pretest trial, participants completed 16 practice trials and were assigned to one of four groups: internal focus (attention on arm movement), proximal external focus (attention on lights), distal external focus (attention on a green cone), or control (no focus instruction). Twenty-four hours later, participants completed retention and transfer tests (three trials each), with the transfer test involving a change in the light stimulus color. Results: The internal focus group showed significantly worse performance than the proximal and distal external focus groups, as well as the control group, across the practice, retention, and transfer phases. Discussion: An internal focus of attention may disrupt motor learning by overloading cognitive processes or interfering with automatic control mechanisms. In contrast, external foci appear to support more efficient motor learning. Conclusion: The findings suggest that encouraging an external focus of attention—either proximal or distal—enhances motor skill learning in adolescents, while an internal focus may be detrimental. These insights can inform instructional strategies in educational and sports settings.

This paper suggests the energy efficiency of automatic street lights using Arduino. The main goal is to efficiently design energy streetlights for current rural streetlights, urban areas and fully intelligent cities. The systems are LEDs, solar panels, load control, battery, and Arduino. The system is set to automatically eliminate during the day and operate only at night. I have a strong basis for Python programming, which combines practical experience, a proactive approach to solutions, and a true enthusiasm for establishing effective solutions. The proposed system consists of an automatic lighting control mechanism with solar panels, battery storage units, a load controller, and slight dependent resistors (LDRs) and microcontrollers. In sunlight, solar panels convert sunlight into electrical energy and store it in a battery. When the ambient light decreases at dusk, the LDR recognizes the waste of brightness and directs the Microcontroller to turn on the LED street lantern. Similarly, the system automatically turns off the lights at dawn, ensuring efficient energy use.

Chest radiography remains a cornerstone of pediatric pneumonia diagnosis, offering a non-invasive approach. However, minimizing radiation exposure in children is crucial. This study aimed to optimize pediatric X-ray doses by developing a prototype for an automatic tube voltage control system in conventional X-ray machines. We identified key factors influencing radiation dose during pediatric chest X-rays. Utilizing the Commission of European Communities' recommended tube voltage (>60 kVp), we analyzed the Entrance Surface Dose (ESD). Subsequently, an automatic control mechanism for tube voltage (<60 kVp) was constructed using a ZMPT101B voltage sensor, a control unit, and a patient-type selector. The ZMPT101B sensor detects preset tube voltage. A dedicated algorithm analyzes these values, and if they exceed recommended levels, the control unit adjusts them. Results are displayed on a Liquid Crystal Display (LCD). Validation of ESD with varying tube voltage and current settings confirmed that exposure time and tube voltage significantly impact ESD more than tube current. Lower kVp settings with high tube currents are unsuitable for children due to the limited penetration depth of such photons, resulting in higher tissue absorption without improving image quality. This novel monitoring system addresses this concern by automatically adjusting tube voltage for optimal image acquisition at reduced dose levels.

Suppressing spurious oscillations is crucial for designing reliable high-order numerical schemes for hyperbolic conservation laws, yet it has been a challenge actively investigated over the past several decades. This paper proposes a novel, robust, and efficient oscillation-eliminating discontinuous Galerkin (OEDG) method on general meshes, motivated by the damping technique (see J. Lu, Y. Liu, and C. W. Shu [SIAM J. Numer. Anal. 59 (2021), pp. 1299–1324]). The OEDG method incorporates an oscillation-eliminating (OE) procedure after each Runge–Kutta stage, and it is devised by alternately evolving the conventional semidiscrete discontinuous Galerkin (DG) scheme and a damping equation. A novel damping operator is carefully designed to possess both scale-invariant and evolution-invariant properties. We rigorously prove the optimal error estimates of the fully discrete OEDG method for smooth solutions of linear scalar conservation laws. This might be the first generic fully discrete error estimate for nonlinear DG schemes with an automatic oscillation control mechanism. The OEDG method exhibits many notable advantages. It effectively eliminates spurious oscillations for challenging problems spanning various scales and wave speeds, without necessitating problem-specific parameters for all the tested cases. It also obviates the need for characteristic decomposition in hyperbolic systems. Furthermore, it retains the key properties of the conventional DG method, such as local conservation, optimal convergence rates, and superconvergence. Moreover, the OEDG method maintains stability under the normal Courant–Friedrichs–Lewy (CFL) condition, even in the presence of strong shocks associated with highly stiff damping terms. The OE procedure is nonintrusive, facilitating seamless integration into existing DG codes as an independent module. Its implementation is straightforward and efficient, involving only simple multiplications of modal coefficients by scalars. The OEDG approach provides new insights into the damping mechanism for oscillation control. It reveals the role of the damping operator as a modal filter, establishing close relations between the damping technique and spectral viscosity techniques. Extensive numerical results validate the theoretical analysis and confirm the effectiveness and advantages of the OEDG method.

Design and implementation of an automatic speed control mechanism using arduino, RFID, GPS, and MATLAB for enhancing safety near Schools and Colleges

Abstract: Accidents have become increasingly common in recent times, primarily stemming from driver inattentiveness during their journeys. These accidents result in significant financial losses and a high number of fatalities, in addition to causing harm to the environment. This paper outlines a module designed to alert drivers by implementing a straightforward monitoring system. Through our analysis, it has become evident that more than 25% of accidents can be attributed to driver drowsiness, emphasizing the grave danger it poses, even surpassing the risks associated with drunk driving. To detect driver drowsiness, a simple camera system is employed, which initiates monitoring as soon as the car starts and continues throughout the journey. This monitoring system is closely linked with an automatic speed control mechanism, resembling an automatic speed controller. The paper elaborates on the techniques used to assess driver safety by examining visual cues from the driver, ultimately serving as an early warning system for potential accidents. Consequently, reducing speed is made more straightforward, with alerts provided to the driver, ultimately leading to a decrease in accidents caused by driver drowsiness thanks to our proposed approach

With the rapid advancement of technology, smart devices like refrigerators have become integral parts of modern living. In this context, our proposed model aims to enhance refrigerator functionality by incorporating features for food quantity detection, temperature monitoring, and spoilage reminders. This system utilizes a mobile application interface to provide users with real-time information regarding the quantity of food items in the refrigerator and the current temperature. By leveraging this data, users can efficiently plan their meals, reduce food wastage, and optimize energy consumption through automatic control mechanisms. Additionally, the system incorporates a spoilage reminder feature, alerting users to food items in air-tight containers that may spoil without emitting detectable odours. This comprehensive approach to refrigerator management not only enhances convenience but also promotes sustainability by minimizing food waste and energy usage. Keywords— - Embedded system, Internet of things, DHT11, IR detector, Arduino Uno

Joint non-fragile automatic generation control and multi-event driven mechanism co-design for wind integrated power system under denial of services attacks

As cities worldwide transform into smart, interconnected urban environments, the management of municipal waste emerges as a pressing challenge. This paper, titled "Development of a Smart Waste Management System with Automatic Bin Lid Control," offers a sophisticated solution that integrates seamlessly within the concept of smart cities. This system harnesses the power of the Internet of Things (IoT) to optimize waste collection and enhance urban cleanliness. The primary aim of this project is to create a smart waste management system that extends beyond traditional waste bins. It introduces a network of intelligent waste containers equipped with automatic lid control mechanisms that operate based on real-time waste level data. When approaching these bins, the lid control mechanism automatically opens the bin only if the waste level is not full, thereby facilitating convenient waste disposal. In the context of smart cities, this innovative approach presents several advantages. It optimizes waste collection efficiency by prioritizing bins in need of immediate attention and ensures that waste containers are not prematurely emptied, reducing unnecessary waste disposal trips. Moreover, the system enables city authorities to gain insights into waste level trends, fostering data-driven and proactive waste management strategies for a cleaner, more sustainable urban environment.

Quantum neural networks (QNNs) leverage the strengths of both quantum computing and neural networks, offering solutions to challenges that are often beyond the reach of traditional neural networks. QNNs are being used in areas such as computer games, function approximation, and big data processing. Moreover, quantum neural network algorithms are finding utility in social network modeling, associative memory systems, and automatic control mechanisms. Nevertheless, ensuring the reliability of quantum neural networks is crucial as it directly influences network performance and stability. To investigate the reliability of quantum neural networks, this paper proposes a methodology wherein operator measurements are performed on the final states of the output quantum states of a quantum neural network. The proximity of these measurements to the target value is compared, and the fidelity value, combined with a quantum gate operation, is utilized to assess the reliability of the quantum neural network. Through network training, the results demonstrate that, under optimal parameters, both the fidelity of the final state measurement value and the target value of the model approach are approximately equal to 1. It indicates that training mitigates the errors stemming from encoding into the initial quantum state, thereby resulting in enhanced system reliability and accuracy.

The W-MON project goal is to establish an automatic control mechanism of the presence of radioactive material in conventional waste containers at CERN using a distributed network of interconnected low-power radiation sensors. This network facilitates continuous data recording, transfer and storage in a database while allowing online and offline data analysis, in addition to alarm triggering. Data transmission, processing and evaluation is achieved by a centralized IoT end-to-end data architecture that has been developed for real-time monitoring and visualization of the radiation levels in waste containers. In this paper the results of field tests of the W-MON system described in two previous papers are presented for three different types of sensors. Estimation of failure detection probability, long-term stability tests and sensitivity studies carried out using radioactive samples of various activities placed in standard waste containers are described. A comparison between the manual monitoring procedure currently used at CERN and the W-MON system is discussed in detail.

Distributed resilient fault-tolerant cooperative automatic generation control and multi-event triggering mechanism co-design for wind energy conversion power system

In recent years, there has been a growing movement in Western countries toward the abolition of gonadal protection during radiography. The reasons for this recommendation are that there are few reports of increased risk of genetic effects, that the ovarian dose is not due to direct X-rays but due to internally scattered X-rays that cannot be shielded, and that the presence of gonadal protection may adversely affect the automatic exposure control mechanism and may mask important findings. In addition, the gonadal protection is a large high absorber of X-rays, and its presence in the irradiation field may have some effect on image quality, but the effect of the gonadal protection on image quality has not been clarified. In addition, after the abolition of gonadal protection, the optimal irradiation field setting is expected to become even more important to avoid unnecessary exposure. In this study, we investigated the effect of gonadal protection on image quality in frontal hip radiographs of adults with different radiation qualities and clarified the image quality under conditions in which the irradiation field is appropriately narrowed. Frontal hip radiographs were taken using a human phantom as the subject, and the image quality of the femoral head was evaluated. Two irradiation fields were used: (a) 14×17 inch field and (b) an appropriate field (11.6×15 inch) that does not impair the reference line and image information necessary for reading hip joint images. The imaging tube voltage was set at 70 kV, and conditions for adding a copper filter were also considered. The incident surface air kerma was set to 1.25 mGy. The incident surface dose at this time was sufficiently lower than the diagnostic reference level (2.5 mGy) in Japan and was judged to be appropriate for imaging using an indirect conversion flat panel detector. The image quality evaluation item was the signal difference to noise ratio (SdNR) including scatterers. The SdNR decreased by 4.6% when a gonadal shield was placed, indicating that the gonadal shield reduced image quality. When the irradiation field size was appropriately narrowed down, SdNR slightly increased or decreased depending on the quality of the imaging material, but the change was small compared to the change in SdNR with and without the gonadal protection shield. The results of this study confirm that the elimination of gonadal protection in hip radiography has significant advantages, such as reducing unnecessary X-ray exposure while ensuring image quality, when the irradiation field is set appropriately.

Abstract This article emphasizes the intermittent characteristics of renewable energy sources (RESs) and explores the role of forecasting in improving the performance of the automatic generation control (AGC) mechanism of the interconnected power system. Due to hybridization of power system basic AGC controller (PID, TID, and ID‐T) are insufficient to stabilized the system parameters. So, a new type of fractional order integral tilted derivative controller (FIDN‐T) has been proposed, which give better performance in terms of settling time, undershoot and overshoot in case of RESs with real data forecasting also. FIDN‐T has been compared with some existing controller which give the results better than basic controller. In order to optimize the different parameters of the proposed controller, a new modified Opposition‐based Sea‐horse Optimization (OSHO) algorithm has been proposed. The OSHO is compared with a few existing, well‐known meta‐heuristic algorithms to show its superiority. The analysis has been conducted under different operating conditions, including step and random disturbances as well as the IEEE‐39 bus, to verify the robustness as well as adaptability of the suggested controller. The comprehensive results of the studies provide strong evidence in support of the effectiveness and efficacy of the suggested control methods and suggest that it has the potential to be implemented in real‐world power systems for improved performance and stability.

The internal inspection of fabrics is one of the most important phases of production in order to achieve high quality standard in the textile industry. Therefore, developing efficient automatic internal control mechanism has been an extremely major area of research. In this paper, the famous architecture Googlenet was fine-tuned into two configurations for texture defect classification that was trained on a textile texture database (TILDA). The experimental result, for both configurations, achieved a significant overall accuracy score of 97% for motif and a non-motif-based images and 89% for mixed images. In the results obtained, it was observed that the second model, which updates the last six layers, was more successful than the first one; which updates the last two layers.

In the commercial and industrial sectors, automatic robotic control mechanisms, which include robots, end effectors, and anchors containing components, are often utilized to enhance service quality. Robotic systems must be installed in manufacturing lines for a variety of industrial purposes, which also increases the risk of a robot, end controller, and/or device malfunction. According to its automated regulation, this may hurt people and other items in the workplace in addition to resulting in a reduction in quality operation. With today's advanced systems and technology, security and stability are crucial. Hence, the system is equipped with fault management abilities for the identification of developing defects and assessment of their influence on the system's activity in the upcoming utilizing fault diagnostic methodologies. To provide adaptive control, fault detection, and state estimation for robotic automated systems intended to function dependably in complicated contexts, efficient techniques are described in this study. This paper proposed a fault detection and state estimation using Accelerated Gradient Descent based support vector machine (AGDSVM) and gaussian filter (GF) in automatic control systems. The Proposed system is called (AGDSVM + GF). The proposed system is evaluated with the following metrics accuracy, fault detection rate, state estimation rate, computation time, error rate, and energy consumption. The result shows that the proposed system is effective in fault detection and state estimation and provides intelligent control automatic control.

The analysis of the center of pressure (CoP) trajectory, derived from force platforms, is a widely accepted measure to investigate postural balance control. The CoP trajectory could be analyzed as a physiological time-series through a general stochastic modeling framework (i.e., Stabilogram Diffusion Analysis (SDA)). Critical point divides short-term from long-term regions and diffusion coefficients reflect the level of stochastic activity of the CoP. Sample Entropy (SampEn) allows quantifying the CoP complexity in terms of regularity. Thus, this study aimed to understand whether SDA and SampEn could discriminate the neuromuscular control mechanisms underpinning static and dynamic postural tasks. Static balance control and its relationship with dynamic balance control were investigated through the CoP velocity (Mean Velocity) and the area of the 95th percentile ellipse (Area95). Balance was assessed in 15 subjects (age: 23.13 ± 0.99 years; M = 9) over a force platform under two conditions: static (ST) and dynamic, both in anterior-posterior (DAP) and medio-lateral (DML) directions. During the DAP and DML, subjects stood on an unstable board positioned over a force platform. Short-term SDA diffusion coefficients and critical points were lower in ST than in DAP and DML (p < 0.05). SampEn values resulted greater in ST than in DAP and DML (p < 0.001). As expected, lower values of Area95 (p < 0.001) and Mean Velocity (p < 0.001) were detected in the easiest condition, the ST, compared to DAP and DML. No significant correlations between static and dynamic balance performances were detected. Moreover, differences in the diffusion coefficients were detected comparing DAP and DML (p < 0.05). In the anterior-posterior direction, the critical point occurred at relatively small intervals in DML compared to DAP (p < 0.001) and ST (p < 0.001). In the medio-lateral direction, the critical point differed only between DAP and DML (p < 0.05). Overall, SDA analysis pointed out a less tightly regulated neuromuscular control system in the dynamic tasks, with closed-loop corrective feedback mechanisms called into play at different time intervals in the three conditions. SampEn results reflected more attention and, thus, less automatic control mechanisms in the dynamic conditions, particularly in the medio-lateral task. The different neuromuscular control mechanisms that emerged in the static and dynamic balance tasks encourage using both static and dynamic tests for a more comprehensive balance performance assessment.

Hydroelectric power plants are the insurance of the interconnected system in order to provide fast energy to the system compared to other fossil fueled power plants. Hydroelectric power plants control the balance between the energy it supplies to the interconnected system and the pressurized water it uses with a system based on the fully automatic control principle. The quality of the energy supplied to the interconnected system depends entirely on this automatic control mechanism. In this study, mathematical models of the mechanisms that affect the automatic control system during the generation of energy in hydroelectric power plants are formed. Transfer functions of the obtained mathematical models are calculated by laplace transform. With the calculated transfer functions, the responses of the units of a hydroelectric power plant to the change of the amount of energy produced under different operating conditions are determined. The obtained data are compared with the actual conditions in a 1330 MW hydroelectric power plant with 8 Francis turbines. It is seen that the mathematical model and the turbine responses in real conditions are similar. In the calculations made at 115, 125, 135, 145 m. net head, the best stability conditions were obtained at 135 m. In addition, as a result of the calculations obtained under different operating conditions, ideal operating conditions are determined to minimize the fluctuations in energy production.

Disaggregated computing has been widely investigated to support the continuous progress in computing performance and overcome the slowdown of Moore’s law. It involves a flexible and optimal interconnection of heterogeneous compute nodes, such as the CPU, GPU, xPU, memory, and storage, to offer an efficient computing environment for various applications. Such a scheme inherently requires high network performance, including low latency, high capacity, determinism, and energy efficiency, all of which are simultaneously achieved through the introduction of optical-layer switching. This paper presents the application of optical-layer-switching architectures to disaggregated computing. Networks associated with disaggregated computing are classified into intra- and interserver networks. Focusing on the intraserver network, a holistic concept of optically composable disaggregated computing (OCDC) is discussed, along with its technological direction toward future digital infrastructure (i.e., the computing continuum). To realize OCDC, scalable and flexible optical switch technologies, as well as their dynamic and automatic control and management mechanisms, are indispensable. Previous studies have reported 32 × 32 silicon photonic switches that can form a nine-stage Clos topology with a radix of 131,072 and a machine-processable function description model for optical-layer switching, called the functional block-based disaggregation model (FBD model) that is capable of automating the operation, administration, and management of any optical physical topology in cooperation with upper-layer operating systems. This study examines their applicability to OCDC. The superior energy performance and scaling of an OCDC system equipped with optical matrix switches, such as silicon photonic switches, with respect to the conventional one big electrical packet-switching approach based on the reported wall-plug power consumption is also presented. The potential applicability of the FBD model as an essential control and management system for the optical layer of OCDC is evaluated through numerical experiments.