Control System Research Articles

An Optimized Multi-Level Control Method for Wireless Power Transfer System Using the Particle Swarm Optimization Algorithm

A Wireless Power Transfer (WPT) system, known for its contactless power delivery, is extensively used for power supply in spacecraft applications. Achieving efficient and stable power transfer necessitates the integration of DC/DC converters on both the primary and secondary sides of WPT systems for power conversion and control. Traditional efficiency optimization methods primarily focus on impedance matching within the wireless power resonance network, often neglecting the overall efficiency optimization of multi-stage DC-DC and WPT systems. This oversight results in suboptimal overall system efficiency despite optimal efficiency in the wireless transmission segment. Additionally, the time-varying nature of mutual inductance and load parameters during power transmission in WPT systems presents challenges for maximum efficiency tracking and power control. This paper introduces a multi-level coordinated control efficiency optimization method for WPT systems utilizing the particle swarm optimization (PSO) algorithm. This method takes into account the transmission losses across all power conversion units within the WPT system, establishing a mathematical model for the joint optimization of overall system transmission efficiency and power. The PSO algorithm is then employed to solve this optimization model using estimated mutual inductance and load values. By adjusting the DC/DC converters on both sides, the method ensures optimal overall system efficiency and consistent power transmission. Experimental results indicate that under varying load and mutual inductance conditions, a Series–Series (SS) compensated WPT system using this method achieves a 200 W power output with maximum efficiency tracking, a power output error of 0.63%, and an average transmission efficiency of 86.2%. This demonstrates superior power transmission stability and higher efficiency compared to traditional impedance matching methods.

Automation in Agriculture: A Robotic Approach to Weed Control for Greenhouse Cucumber Cultivation

The increasing global population has heightened the demand for efficient food production, leading to the adoption of compact cultivation methods such as greenhouses. However, weed growth within these controlled environments significantly challenges crop productivity. The application of robots can be a useful and economic choice. This study presents an innovative, purely mechanical system for weed control in greenhouses, specifically designed to operate autonomously on a monorail. The machine stops in the distance between the two main plant rows (cucumber) and its arm goes into the gap to deploy the weeds by rotating its blades. This is continued repeatedly. The cutting is by the rotational speed of the blade. Variable-speed motions of the blade were at 3500, 2500 and 1500 rpm for 3 types of moulinex, triangular, and circular blades. The movement speed of the arm was 10 and 30 rpm and the forward movement speed of the machine was 30, 40, 50, 60, 80 and 120 rpm. The results showed that different blades, blade speeds and engine speed affect significantly (p <0.05) the percentage of weeds being cut. Although the interactions of these factors have no significant effect on percentage; the average percentages by the blades have significant differences. Although the interactions between these factors were not statistically significant, the comparison of means revealed that at lower blade speeds, the blade type had a pronounced effect on weed-cutting efficiency. As blade speed increased, differences in blade performance diminished. The most effective combination was achieved using Moulinex blades at 3500 rpm with a 10-rpm arm speed, resulting in the highest percentage of weeds cut. These findings suggest that optimizing blade type and speed can significantly enhance the mechanical weed control efficiency in greenhouse environments.

When the Bough Breaks: The Financial Burden of Childbirth and Postpartum Care by Insurance Type.

Out-of-pocket (OOP) costs related to childbirth and postpartum care may cause financial hardship, depending on type of insurance and income. We estimated OOP spending on childbirth and postpartum care and financial strain 1 year after birth, comparing Medicaid-insured births with commercially insured births. The Postpartum Assessment of Health Survey followed up with respondents to the Centers for Disease Control and Prevention (CDC) Pregnancy Risk Assessment Monitoring System after a 2020 birth in six states and New York City. The survey included questions on health care costs and financial well-being. Our analytic sample consisted of 4,453 postpartum people, 1,544 with a Medicaid-insured birth and 2,909 with a commercially insured birth. We observe significant financial hardship from childbirth that persists into the postpartum year, with significant differences by insurance and income. We find Medicaid is highly financially protective relative to commercial insurance; 81.4% of Medicaid-insured births were free to the patient, compared with 15.7% of commercially insured births (p < 0.001). Six of ten commercially insured births (59%) cost over $1,000 OOP. Among respondents reporting OOP costs for childbirth, we found that Medicaid enrollees are more likely to have borrowed money from friends or family to pay for childbirth (8% vs. 1%, p < 0.001) and one in five had not made any payments 1 year postpartum (26% vs. 5% of commercially insured births, p < 0.001). Among the commercially insured, those with incomes under 200% of the federal poverty level (FPL) fared worse financially than those above 200% FPL on a number of indicators, including debt in collection (33% vs. 13%, p < 0.001) and financial worry (55% vs. 34%, p < 0.001). The cost of childbirth and postpartum health care results in significant and persistent financial hardship, particularly for families with lower income with commercial insurance. Medicaid offers greater protection for families with low income by offering reduced cost sharing for childbirth and postpartum health care, but even minimal cost sharing in Medicaid causes financial strain.

Research on Triplex Redundant Flight Control System Based on M1394B Bus

In the modern aviation field, flight control systems’ reliability and safety are paramount. This paper presents a triplex redundant flight control system based on the M1394B bus and designs several key algorithms to enhance system performance. Firstly, a triplex redundant flight control system with a redundant bus structure is constructed based on the characteristics of the M1394B bus. Secondly, a periodic synchronization algorithm with automatic adjustment capabilities is designed to achieve periodic synchronization among the Vehicle Management Computers. An improved voting algorithm based on a sliding window is proposed to enhance the decision-making accuracy and reliability of the control commands output by the flight control system. Additionally, a system reconstruction algorithm is designed to promptly identify and isolate faults, enabling the recovery and reallocation of system resources. Finally, experiments validate the effectiveness of the synchronization algorithm, voting algorithm, and system reconstruction algorithm. The results indicate that the system can effectively address practical engineering challenges and significantly improve reliability and stability. This research provides an essential theoretical foundation and practical reference for the design of future flight control systems for unmanned aerial vehicles and aircraft, holding significant relevance to application.

The Internal Control Management of Chinese Real Estate Industry: A Case Study of Yinfeng Group, Shandong

With the development of China's economy, the number of policy supports provided by SMEs to private enterprises has also increased yearly. Their status and contribution to the national economy cannot be ignored. However, most private enterprises lack an understanding of small and medium-sized enterprises (SMEs) or do not comprehend the internal control mechanisms necessary to formulate and implement an effective internal control management system. This lack of understanding is the main bottleneck preventing enterprises from becoming larger and stronger. Enhancing internal management is particularly beneficial for improving the risk-prevention capabilities of small and medium-sized private enterprises, thereby facilitating their growth. This paper analyzes the problems faced by small and medium-sized private enterprises, using the internal supervision of the internal control system of Yinfeng Group as a case study. Based on internal control's basic and practical meanings, the paper provides suggestions to improve internal control management.

Static actuator-sharing algorithm for concurrent control of multiple plasma properties

Abstract Simultaneous regulation of multiple properties in next-generation tokamaks like ITER and Fusion Pilot Plant (FPP) may require the integration of different plasma control algorithms. Such integration requires the conversion of individual controller commands into physical actuator requests while accounting for the coupling between different plasma properties. This work proposes a tokamak and scenario-agnostic actuator-sharing algorithm (ASA) to perform the above-mentioned command-request conversion and, hence, integrate multiple plasma controllers. The proposed algorithm implicitly solves a quadratic programming (QP) problem formulated to account for the saturation limits and the relation between the controller commands and physical actuator requests. Since the constraints arising in the QP program are linear, the proposed ASA is highly computationally efficient and can be implemented in the tokamak plasma control system (PCS) in real time. Furthermore, the proposed algorithm is designed to handle real-time changes in the control objectives and actuators’ availability. Nonlinear simulations carried out using the Control Oriented Transport SIMulator (COTSIM) illustrate the effectiveness of the proposed algorithm in achieving multiple control objectives simultaneously.

Enhanced Performance of Solar-Powered Dockless E-Scooters on Inclined Roads with Cruise Control Systems

Enhanced Performance of Solar-Powered Dockless E-Scooters on Inclined Roads with Cruise Control Systems

Institutional cooperation in handling epidemics: The case of the Misericordia of Florence during the Italian preunification period

The function of nonprofit organisations (NPOs) in managing healthcare and poverty relief and the role of accounting and reporting in their management control systems have many implications for accounting historians. The present research examines the relationship between NPOs and local governments in the management of public services, particularly during health emergencies. Specifically, this study examines the institutional cooperation between the Grand Duchy of Tuscany, the Misericordia of Florence and the Santa Maria Nuova Public Hospital during the cholera epidemic of 1855–1862. This research applies a conceptual framework based on Michel Foucault's concepts of ‘governmentality’, ‘nosopolitics’ and the ‘government of the poor’ and Mitchell Dean's ‘technologies of government’ to the study of archival primary sources. This research makes several contributions to the accounting history literature regarding the involvement of NPOs in healthcare, including an original analysis of the role of accounting and reporting in the ‘government of the sick’ from a nosopolitical perspective.

Enhanced Curvature-Based Fabric Defect Detection: A Experimental Study with Gabor Transform and Deep Learning

Quality control at every stage of production in the textile industry is essential for maintaining competitiveness in the global market. Manual fabric defect inspections are often characterized by low precision and high time costs, in contrast to intelligent anomaly detection systems implemented in the early stages of fabric production. To achieve successful automated fabric defect identification, significant challenges must be addressed, including accurate detection, classification, and decision-making processes. Traditionally, fabric defect classification has relied on inefficient and labor-intensive human visual inspection, particularly as the variety of fabric defects continues to increase. Despite the global chip crisis and its adverse effects on supply chains, electronic hardware costs for quality control systems have become more affordable. This presents a notable advantage, as vision systems can now be easily developed with the use of high-resolution, advanced cameras. In this study, we propose a discrete curvature algorithm, integrated with the Gabor transform, which demonstrates significant success in near real-time defect classification. The primary contribution of this work is the development of a modified curvature algorithm that achieves high classification performance without the need for training. This method is particularly efficient due to its low data storage requirements and minimal processing time, making it ideal for real-time applications. Furthermore, we implemented and evaluated several other methods from the literature, including Gabor and Convolutional Neural Networks (CNNs), within a unified coding framework. Each defect type was analyzed individually, with results indicating that the proposed algorithm exhibits comparable success and robust performance relative to deep learning-based approaches.

Improving the Dynamics of an Electrical Drive Using a Modified Controller Structure Accompanied by Delayed Inputs

This paper presents the operation of a modified speed controller with a standard PI/PID structure that includes the preprocessing of the controller’s input signal, focusing on the past behavior of control errors. The modification involves adding a delay line, with the outputs of the individual line segments summed with a weighting method, as detailed in the paper. One of the significant advantages of this method is its use of a standard industrial controller structure, which makes it highly practical and easily implementable in existing systems. By relying on well-established control frameworks, this approach reduces the need for specialized hardware or complex modifications, allowing for smoother integration and lower implementation costs. The delay-based signal shaping shows excellent properties for the electric drive system powered by a hard-switching PWM converter. The set of weighted delays acts as a filter whose parameters are chosen using the quality function to test different configurations for optimal performance. When tested in a speed control system for a Permanent Magnet Synchronous Motor, the modifications improved the control quality index, indicating better performance and efficiency. Importantly, the system allows for reducing or eliminating the gain in the differentiating part of the controller, which decreases motor current chattering and noise. This paper includes an experimental verification of the proposed solution in a laboratory setting under semi-industrial conditions.

Investigation on influence factors of optically controlled electrorheological fluid damping system

Abstract Electromagnetic rheological damping control system, as an important control technology, has been widely used in braking, vibration reduction and micro-valve etc. However, the electromagnetic rheological damping control system faces issues of electromagnetic interference due to the high voltage source. To solve this problem, we proposed a novel optically controlled electrorheological fluid damping system. Previous studies have confirmed the feasibility of the optically controlled electrorheological fluid damping control system via numerical simulation and experiment. In this paper, the mechanism and mathematical model of the optically controlled electrorheological fluid damping system are established. The influence factor analyses of the optically controlled damping system, especially the impact of light intensity and microchannel size on system performance, are carried out through experimental and theoretical methods. The research findings of influence factors contribute to a deeper understanding of the working principle of the electrorheological fluid damping system, thereby promoting stability and reliability in microfluidics technology.&amp;#xD;

Evaluation of Control Activities in the Inventory Purchasing System (Case Study at PT. GSI)

Purchasing inventory is a critical aspect of the production process in any company. PT GSI conducts purchasing from suppliers to meet its production needs. This research aims to evaluate the control activities of the inventory purchasing system implemented at PT GSI. Using a qualitative approach, interviews were conducted with relevant departments to gather data. The study evaluates the system based on the COSO framework, which revealed several inconsistencies. A significant finding is that there is no adequate separation of duties at PT GSI, with administrative and financial tasks often handled by the same staff. Additionally, there is a lack of access control to the system, as tasks are still performed manually without sufficient safeguards. The research suggests that improvements are needed in terms of task separation and system access control to align with COSO standards. Implementing these improvements would help PT GSI minimize risks such as fraud and operational inefficiencies. Moreover, operational control would be better facilitated, ensuring smoother processes without interruptions. This study emphasizes the importance of internal control systems, especially in purchasing operations, to prevent potential financial and reputational losses. Ensuring compliance with COSO and other industry standards would enhance the company's overall operational effectiveness.

Fault in Converter Interfaced Micro Grid Using Detection and Identification of Hybrid Technique

ABSTRACTThis paper introduces a novel hybrid approach, termed ZOA‐SNN, for fault detection and identification in converter‐interfaced microgrids. By integrating the Zebra Optimization Algorithm (ZOA) with Spiking Neural Network (SNN) technology, the proposed method provides a comprehensive solution suitable for both grid‐connected and autonomous microgrid operation scenarios. The technique effectively isolates faults in the microgrid while maintaining operation continuity, particularly in islanded conditions. When operating in grid‐connected mode, distributed generators (DGs) provide electricity as needed. When the grid is not available, power sharing amongst DGs is controlled by voltage angle droop control. By isolating malfunctioning portions, the proposed protection system reduces load shedding, while DG control guarantees smooth islanding and resynchronization. Evaluation on the MATLAB platform demonstrates the superior performance of the proposed technique compared to existing algorithms such as Augmented Lagrangian Particle Swarm Optimization (ALPSO), Graph Convolutional Network (GCN), and Buffalo Optimization (BO). With an accuracy, recall, precision, and F1‐score reaching 98.5%, 99.2%, 99.1%, and 99.1%, respectively, the ZOA‐SNN approach excels in fault detection and classification. Additionally, it significantly reduces computation times for parameter calculation, enhancing efficiency in microgrid control systems. These results highlight the innovation and advantages of the ZOA‐SNN approach in enhancing the reliability and efficiency of fault detection systems in microgrid environments.

Hovering Control on a Variable-Parameters Model of a Small Unmanned Helicopter Based on a Backstepping Sliding Mode Method

In order to strengthen the hovering precision of a small unmanned helicopter with a manipulator for completing a hovering operation, in this study, a double-loop control strategy of position and attitude is designed. In the position loop, a sliding mode controller is proposed. It attains high precision and strong robustness under continuous disturbance. With the manipulator continuously operating during helicopter hovering, the overall center of gravity and the moment of inertia of the system will also change. Therefore, a backstepping sliding mode controller is proposed in the attitude loop for controlling the hovering attitude of the helicopter. The high precision and strong robustness of the control system are proven. The digital simulation presents a position steady-state error of less than 2% under constant disturbance, and the hovering attitude angle fluctuation amplitude of the helicopter is less than 0.05 rad.

Control of Large Wind Energy Converters for Aeroacoustic Noise Mitigation with Minimal Power Reduction

The population is often opposed to wind turbines being erected near their homes, mainly because the machines are noisy, especially at night. In an effort to establish a compromise between the needs of the people and the fulfilment of energy demands, wind turbines have the ability to switch between day and night operation by reducing the rotation speed during the night, resulting in a loss of generated power. The present study investigates simple models for noise emission, propagation, and prediction, with the objective of proposing a control system configuration that continuously adjusts the rotational speed as much as necessary until it matches sound level regulations while minimising power losses. Thus, several approaches are implemented and tested with a very large reference wind turbine. The simulation results of a reference wind turbine show that the approaches provide significant improvements in sound reduction as well as in power conversion.

Control of the Motion of an Inverted Spherical Pendulum on a Moving Base. Hybrid Impact Approach

A new hybrid method for the construction of control actions of a linear control system with constant coefficients is considered in this paper. It is assumed in this paper that a part of the discussed system meets some conditions. Some states of the main system are considered to be control actions for a subsystem for which and LQR stabilizer is acquired. Then, those control actions of the subsystem are used to construct the control actions for the main system. In the problem of controlling the motion of a complex linear system of an inverted spherical pendulum on a moving base, a new approach to the construction of control actions (hybrid action method) was used. It is assumed that a component of the complex system under discussion satisfies certain conditions. The inertial forces at the center of mass of the base of the composite system are considered to be the controlling influences on the inversion of the pendulum, for which the LQR stabilizer was purchased. The determined internal control actions on the inverted pendulum are then used to construct external control actions on the base of the composite system. In the end, a numerical analysis was carried out.

Feature-weighted Random Forest with Boruta for Fault Diagnosis of Satellite Attitude Control Systems

The performance of random forest (RF) based satellite attitude control system (ACS) fault diagnosis methods is limited by uninformative features in high-dimensional data. To solve this problem, we proposed a feature-weighted random forest with Boruta (FWRFB) based fault diagnosis method is proposed for fault diagnosis of ACSs. Firstly, a Boruta feature selection algorithm is used to obtain a feature set and determine significant feature weights. Subsequently, a novel feature-weighted random forest (FWRF) algorithm is designed, which utilizes feature-weighted random sampling instead of simple random sampling to generate feature subsets in the RF. The FWRFB effectively utilizes the feature information while mitigating noise interference. Finally, a FWRFB-based diagnostic module is developed for online fault diagnosis of ACSs. The effectiveness of the proposed method is verified by the ACS data from a semi-physical simulation platform.

Robust Adaptive Control System of Variable Sampling Period for Cement Raw Mix Quality Control

The advanced quality control of the raw mix remains a priority for the cement industry, particularly in recent years, where large quantities of alternative fuels and raw materials are used in clinker production, aiming to reduce the CO2 footprint. This study presents an adaptive control system with a variable sampling period for regulating raw mix quality in the raw mill (RM) output in a process with four independent inputs and four outputs: the lime saturation factor (LSF), silica modulus (SM), alumina modulus (AM), and SO3. The three pillars of the system are (1) mill dynamics calculation using exclusively industrial data, (2) the design of the controllers to meet robustness criteria, and (3) performance enhancement through simulators. Our technique periodically adjusts the gains of the controllers based on the mill’s dynamic parameters, which are computed from raw mix laboratory analyses. The presented results correspond to more than 14,000 h of mill operation. The standard deviation of the LSF at the mill outlet ranged from 1.5 to 3, which is equivalent to 1 to 2 standard deviations of LSF reproducibility. The standard deviation of the other moduli was close to the corresponding reproducibility of each. The presented adaptive gain-scheduling controller for LSF can be applicable to a broad range of raw meal grinding systems.

Lightweight authentication scheme for edge control systems in Industrial Internet of Things

Lightweight authentication scheme for edge control systems in Industrial Internet of Things

EFEKTIVITAS SISTEM PENGENDALIAN INTERNAL TERHADAP PERSEDIAAN BARANG DAGANG DI CV MM ACING JAYA TUATUNU PANGKALPINANG

This thesis, written and compiled by Jessintha Sherly Tabita with Student Identification Number 540200024, is titled “Effectiveness of the Internal Control System on Merchandise Inventory at CV MM Acing Jaya Pangkalpinang." The study aims to understand the internal control system over merchandise inventory at MM Acing Jaya Pangkalpinang. Data collection techniques included observation, interviews, and documentation. The data analysis technique used was descriptive-qualitative. The results show that the internal control system over merchandise inventory at MM Acing Jaya Pangkalpinang is largely in accordance with the theoretical standards of COSO Most of the components of the control environment are in place, but they have not been effectively implemented due to the absence of documents regulating the control environment. The control activities are also in place but not effective, as there are still frauds outside the store's supervision committed by drivers. Information and communication are in place but not yet effective, as some documents are still difficult to locate when needed.