Control Technique Research Articles

Primary side control technique for capacitive power transfer system without any wireless feedback

The output voltage of capacitive power transfer (CPT) system will change if the load resistance is varied. This paper presents a method to regulate the output voltage using a controller that is located on the primary side, known as the primary side control technique. It does not require any additional components and wireless feedback, which lowers the cost and complexity of CPT system compared to the conventional control technique. Instead of directly measuring the output voltage on secondary side, it is estimated through the measured capacitor voltage on primary side. Modified sine wave control of the full-bridge inverter is adopted to regulate the output voltage. The proposed control technique is validated by the simulation via PSIM software using the practical parameters of capacitive coupler presented in the literature. Simulation results of the output voltage control against the step change in desired output voltage and load resistance indicate the performance of proposed control technique.

Innovative Hierarchical Control of Multiple Microgrids: Cheetah Meets PSO

The expansion of microgrids (MGs) comes from the increasing integration of renewable energy resources (RES) and energy storage systems (ESs) into distribution networks. However, effective integration, coordination, and control of Multiple Microgrids (MMGs) during energy transition from microgrid to grid, and vice versa presents a formidable challenge. This arises from the necessity to ensure smooth operation, coordination, and control of MMGs for stability and efficiency during transitions. The dynamic operation of MMGs due to intermittent renewable energy in microgrids and load variations presents an additional challenge for hierarchical control techniques.This paper provides an Artificial Intelligent (AI)-based control technique and introduces an innovative hybrid optimization technique, denoted as HYCHOPSO, derived from the fusion of Cheetah Optimization (CHO) and Particle Swarm Optimization (PSO) techniques, and the quantitative findings of extensive benchmark testing, constitute key aspects of novelty. The strategic choice of this novel optimization technique, coupled with a Proportional-Integral (PI) controller, provides key insights.HYCHOPSO is tested within benchmark functions and reaches its optimal score before 50 iterations as compared with optimization algorithms namely CHO, GWO, PSO, Hybrid-GWO-PSO, and SSIA-PSO which reaches after approximately 200 iterations. HYCHOPSO consistently exhibits the lowest mean values, indicating its robust convergence capabilities.The proposed control technique results in a significant reduction of the microgrid's Current Total Demand Distortion to 1.1%, meeting acceptable limits for a 600V-bus According to IEEE519-2014 standard, even under nonlinear loads. Additionally, precise regulation of voltage and frequency is achieved with0.19%−+ deviations and a frequency overshoot of 1.9%. Furthermore, optimization contributes to seamless energy transition from microgrid to grid, achieving synchronization in less than 5 milliseconds. This enhances the real application's reliability, flexibility, scalability, and robustness. Furthermore, HYCHOPSO is introduced as an AI-based technique to facilitate control parameter design under dynamic conditions, with substantial simulation cases demonstrating control feasibility

Nonlinear control of three level NPC inverter used in PV/grid system: comparison of topologies and control methods

With the passage of time, the importance of using renewable energy systems to overcome energy consumption and improve the quality of the grid has emerged through the use of nonlinear control techniques and reliance on advanced types of inverters such as multi-level inverters. This research is focused on comparing two grid-connected converter topologies in a photovoltaic (PV) generation system connected to a three-phase grid that serves a non-linear load. Additionally, the study explores two different control techniques applied to this converter, evaluating their effects on the total harmonic distortion coefficient. A comparison has been made between the traditional inverter and the three-level inverter type neutral point clamped (NPC) inverter, with the use of integral backstepping (IBS) technique which was also compared with the proportional integral (PI) controller. The simulation results in MATLAB/Simulink are presented illustrating the performances and the strong effectiveness of the three-level NPC inverter controlled by the proposed technique (IBS).

New control scheme for a dynamic voltage restorer based on selective harmonic injection technique with repetitive controller

Repetitive controller and selective harmonic injection technique (SHI) in medium and low voltage distribution networks improve dynamic voltage restorer (DVR) DC bus voltages as well as nullify power quality (PQ) problems. DVRs use sinusoidal pulse width modulation (SPWM) firing control, but DC bus use seems to be limited, affecting density, cost, and power packaging. By adding 1/6th of the 3rd harmonic waveform to the basic waveform, SPWM yields the developed model. According to the findings, 15% of DC bus usage improves and produces high voltage AC. Nevertheless, just control systems perturb PQ. The proposed controller uses feed forward and feedback to enhance transient response and justify stable zero error. 3rd third harmonic injection pulse width modulation (THIPWM) improves total harmonic distortion (THD) in the proposed scheme. Power system computer aided design (PSCAD) simulation produced high accuracy for THIPWM and repetitive controllers.

A novel hybrid-fuzzy logic based UVC technique for solar-PV/grid integrated water-pumping system

The continual depletion of fossil fuels and increased green-house emissions are persuading the consumers to install micro-renewable energy sources-based water pumping system. Among numerous energy sources, the solar-PV plays a significant role in water pumping application due to its virtuous, environment friendly, noise-free and abundant nature, so on. Along with solar-PV, the grid integrated system enables the continuous operation of water pumping system during varying temperature and irradiance conditions, and also delivers available solar-PV energy to grid during non-functional of pumping system. The above operations are carried by using bidirectional inverter which is controlled by using unit-vector control (UVC) technique. It consists of proportional-integral controller, which is not suited for regulation of DC-link voltage at desired level because of improper selection of gain values. In this work, an intelligent hybrid-fuzzy logic based UVC technique evidences the intelligent knowledge base for better regulation of DC-link voltage and power-flow of bidirectional inverter. The performance and operation of proposed hybrid-fuzzy logic control UVC technique for solar-PV/Grid integrated water-pumping system is evaluated under various operating cases by using MATLAB/Simulink tool; simulated results are conferred with superlative comparisons.

Experimental investigation of bidirectional series resonant DC-DC converter in different operating modes

This paper presents a study of bidirectional series resonant DC/DC converter. The main operating modes of the converter with phase-shift control technique are observed. An experimental survey with a laboratory model of such type of converter working over the resonant frequency is made. The functionality of the studied device operating in a wide area of loading is demonstrated with waveforms of the main parameters. The conducted measurements are used to build the experimental output characteristics of the converter. A similarity of the experimental results with the theoretical are denoted, and the ability to achieve current source characteristics for the whole range of loading is proven. The possibility of the studied converter for operation both in forward and reverse modes of energy flow is proved, which positions the device as an appropriate variant for implementation in the storage system control area.

Novel control of PV-wind-battery powered standalone power supply system based LSTM based ANN

Integrated wind-photovoltaic (PV) based standalone electric power supply systems are widely used for various applications. A battery storage system is needed to provide continuous power supply to loads despite changes in loads, wind speed, and solar irradiance. Power quality is crucial in these hybrid systems, as the battery needs to charge from surplus power when generation exceeds the load and discharge to meet load demand. A bidirectional DC to DC converter is used to connect the battery to the network, and maximum power point tracking devices with proper algorithms are incorporated for optimal utilization of PV and wind turbines. Multiple PV systems and wind turbines are considered for proper power supply system ratings. Long short-term memory (LSTM) based artificial neural network (ANN) controllers are implemented for various control units in the hybrid standalone power system. The proposed control techniques improve power quality under various situations. Results are presented using MATLAB/Simulink to evaluate the performance of the proposed method.

ANFIS-based optimisation for achieving the maximum torque per ampere in induction motor drive with conventional PI

This research presents an innovative approach to controlling the speed of an induction motor drive by utilizing a combination of neural networks and fuzzy inference systems (ANFIS). The study focuses on computing the rotor's magnetic flux while considering different overshoot and settling criteria for torque and motor speed. The goal is to optimize torque per ampere and generate the necessary torque. The proposed ANFIS-based torque-per-ampere control technique offers a distinctive method applicable to a static induction motor model. This method allows for an increase in stator current while maintaining flexibility and individuality in motor control strategies. It compares various motor vector control methods, specifically focusing on strategies to reduce torque ripple. These strategies include adaptive ANFIS, fuzzy logic control (FLC), and proportional-integral (PI) control. The research highlights the effectiveness of an adaptive ANFIS controller in achieving the most significant reduction in torque ripple within the induction motor system. This proposed problem identification sets the stage for exploring and developing solutions to enhance the performance and efficiency of induction motor drives.

Pole placement tuning of proportional integral derivative feedback controller for knee extension model

Functional electrical stimulation (FES) has shown potential in rehabilitative exercises for patients recovering from spinal cord injuries. In recent developments, conventional open-loop FES control techniques have evolved into closed-loop systems that employ feedback controllers for automation. However, closed-loop FES systems often face challenges due to muscle non-linear effects, such as fatigue, time delays, stiffness, and spasticity. Therefore, an accurate non-linear knee model is required during the design stage, and precise tuning of the feedback controller parameters is vital. A proportional– integral–derivative (PID) controller is commonly used as a feedback controller due to its simplicity and ease of implementation. However, most PID tuning methods are complex and time consuming. This paper investigates the viability of employing the pole placement technique for tuning a PID controller that regulates the non-linear knee extension model. The pole placement method aims to improve the control and adaptability of the PID controller in closed-loop FES systems, specifically by facilitating knee extension exercises. MATLAB Simulink was used to assess the effectiveness of this tuning approach. Results showed that the PID controller performed satisfactorily without non-linearities, but performance varied with the inclusion of specific non-linearities. The pole placement tuning method facilitated preliminary assessments of PID controller performance, preceding highly advanced optimization.

The wind turbine's direct power control of the doubly-fed induction generator

The study suggests a comprehensive approach to modeling and controlling variable-speed wind turbine systems that utilize doubly fed induction generators (DFIGs). To make sure that energy is transferred efficiently between the DFIG rotor and the grid, a two-level inverter with perfect bidirectional switches is used. Using the tip speed ratio algorithm and taking into consideration the randomness in wind speed, the maximum power at the wind turbine is optimized. Then, the control strategy utilizes direct power control (DPC) due to its various advantages. The advantages of employing this control technique are manifold. Firstly, it eliminates the necessity for rotor current control loops. Secondly, it obviates the need for controllers such as PI controllers to manage torque and flux. Furthermore, it has yielded exceptional simulation results when implementing direct power control (DPC) within the MATLAB/Simulink environment, specifically in the context of a doubly fed induction generator (DFIG) wind power system.

Virtual voltage control to redistribute reactive power of generators in a microgrid

The paper examines a strategy for managing voltage control in a microgrid by redistributing reactive power among its distributed generators. Unlike traditional droop control, the new control approach can provide a more accurate reactive power response based on a virtual impedance that helps calculate a virtual voltage. In addition, this virtual impedance is employed for the current controller inverter to improve the results. The adaptive virtual voltage control works well to provide active and reactive power. The proposed control works effectively by balancing the active and reactive power of the grid and maintains the fundamental frequency. The control technique assists the new microgrid (MG) in adapting the operation effectively and redistributing the active and reactive power.

Bidirectional DC-DC Converter and Improved Electrical Vehicle Dynamic Response Control

Background: In automotive applications where bidirectional power flow is necessary to lighten the power system, dual active bridge (DAB) converters are frequently employed. Variations in the required output voltage, erratic input voltage, and shifting loads all have an impact on this converter. As a result, converter performance has to be improved. To increase efficiency, the current stress of the DC-DC converter must be optimised. This paper proposes a control scheme for the coupled inductor bidirectional DC-DC (CIB DC-DC) converter utilising both model predictive control (MPC) and a proportional-integral (PI) controller. The integration of these control techniques aims to enhance the performance and efficiency of the converter. Methods: The MPC algorithm is employed to predict the converter's future behaviour based on a dynamic model, taking into account system constraints and performance criteria. By optimising the control action over a finite time horizon, the MPC algorithm ensures an optimal response, considering the current state and anticipated changes. Additionally, a PI controller is incorporated to augment the control strategy. The proportional component of the PI controller enables a fast initial response to the error between the desired and actual converter outputs. The integral component eliminates steady-state errors and provides robustness against disturbances, resulting in improved overall system performance. Results: The proposed control scheme is implemented and evaluated through simulations and experimental tests on a prototype converter. The results demonstrate the effectiveness of the combined MPC and PI controller approach. Conclusion: The coupled inductor bidirectional DC-DC (CIB DC-DC) converter using MPC can provide precise control of power flow between two voltage domains, enabling efficient bidirectional power transfer. The predictive capabilities of MPC allow it to adapt to varying load conditions and respond quickly to changes, ensuring stable operation and accurate regulation of voltage and current. Overall, the coupled inductor bidirectional DC-DC converter controlled using MPC over PI offers improved performance, efficiency, and flexibility compared to traditional control methods. MPC can handle the complex dynamics response and non-linear characteristics of the converter, making it suitable for bi-directional vehicle charging applications, where precise control and high efficiency can be achieved.

Dynamic Voltage Stiffness Control Technique for a Virtual Oscillator-Based Grid- Forming Controller

Dynamic Voltage Stiffness Control Technique for a Virtual Oscillator-Based Grid- Forming Controller

Evaluation of Optimum MPPT Controllers for PV Cells using Matlab Simulink Platform

Abstract: Nowadays, the Photovoltaic cell is one of the most essential parts in the electrical field to convert photo light to voltage and current, at the desired output voltage and frequency by using various control techniques The Solar panel can produce maximum power at a particular operating point called Maximum Power Point (MPP).To produce maximum power and to get maximum efficiency, the entire photovoltaic panel must operate at this particular point. Maximum power point of PV panel keeps on changing with changing environmental conditions such as solar irradiance and cell temperature. Thus to extract maximum available power from a PV module, MPPT algorithms are implemented. The output power of a photovoltaic (PV) module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement MPPT controllers to obtain the maximum power of a PV system regardless of variations in climatic conditions. This project reviews the most used MPPT algorithms, which are Perturb and observe (P&O), Incremental conductance method (ICM), and Fuzzy logic control (FLC).

Conflict management in garment manufacturing company

Conflict is an imperative issue- even considered as burning issue in many industries- that is inevitably needed to dissolve or minimize in order to operate the organization successfully. Many researches and studies of conflict management have been conducted on several industries, but this researcher eagerly recognized to present an exclusive literature review on garment manufacturing industry not only from theoretical perspective but also based on his valuable long work-experience in this garment industry. It is hypothetically deemed by the garment factory owners and top management in Bangladesh that, somebody should research on this real-world issue in light of his/her acquaintance pertinent to this industry. The main purpose of this literature review is to present the practical and pervasive state of conflict management in garment manufacturing companies, and to find the techniques of resolution according to this researcher’s practical experience. This study provides an extensive literature review on conflict management in the context of Bangladesh garment manufacturing industry. It described meticulously about conflict zones, conflict types, conflict process, and some treasured techniques of conflict control- especially applicable for garment factories. It is amplified that, to control or minimize conflict in garment factory, conflict resolution skills and attributes should be taken into consideration, and top management’s positive intention is required to establish an effective conflict management system. Furthermore, along with the literature review, this study recommends some pragmatic solutions incorporating to different perspectives of conflict patterns and styles, and the guidelines of this study will lead the garment organizations to formulate defacto conflict management strategies for their employees.

Studying the Optimal Frequency Control Condition for Electric Vehicle Fast Charging Stations as a Dynamic Load Using Reinforcement Learning Algorithms in Different Photovoltaic Penetration Levels

This study investigates the impact of renewable energy penetration on system stability and validates the performance of the (Proportional-Integral-Derivative) PID-(reinforcement learning) RL control technique. Three scenarios were examined: no photovoltaic (PV), 25% PV, and 50% PV, to evaluate the impact of PV penetration on system stability. The results demonstrate that while the absence of renewable energy yields a more stable frequency response, a higher PV penetration (50%) enhances stability in tie-line active power flow between interconnected systems. This shows that an increased PV penetration improves frequency balance and active power flow stability. Additionally, the study evaluates three control scenarios: no control input, PID-(Particle Swarm Optimization) PSO, and PID-RL, to validate the performance of the PID-RL control technique. The findings show that the EV system with PID-RL outperforms the other scenarios in terms of frequency response, tie-line active power response, and frequency difference response. The PID-RL controller significantly enhances the damping of the dominant oscillation mode and restores the stability within the first 4 s—after the disturbance in first second. This leads to an improved stability compared to the EV system with PID-PSO (within 21 s) and without any control input (oscillating more than 30 s). Overall, this research provides the improvement in terms of frequency response, tie-line active power response, and frequency difference response with high renewable energy penetration levels and the research validates the effectiveness of the PID-RL control technique in stabilizing the EV system. These findings can contribute to the development of strategies for integrating renewable energy sources and optimizing control systems, ensuring a more stable and sustainable power grid.

Advancing maintenance, monitoring, and control techniques for the optimization of power electronic systems

This paper explores the innovative methodologies and technologies in predictive maintenance, real-time monitoring, fault detection, and advanced control strategies for power electronic devices. Initially, we delve into data acquisition and preprocessing techniques crucial for ensuring the quality and reliability of data used in predictive models. These models, leveraging machine learning and time-series analysis, predict the remaining useful life of devices, guiding proactive maintenance strategies. Furthermore, we discuss the significance of risk assessment and decision support systems in prioritizing maintenance tasks and allocating resources efficiently. The narrative then shifts to real-time monitoring and fault detection, emphasizing the role of sensor integration, data fusion, anomaly detection, and diagnostics in maintaining system integrity. Condition-based maintenance strategies, underscored by real-time data analytics, are presented as a means to optimize maintenance activities and enhance operational performance. The paper concludes with a detailed examination of advanced control strategies, including model predictive control, reinforcement learning, and distributed control and optimization techniques, highlighting their potential to improve system efficiency, reliability, and adaptability. Through comprehensive research and analysis, this work aims to provide valuable insights into the development of sophisticated maintenance and control mechanisms for power electronic systems, ultimately contributing to their longevity and operational efficacy.

Combining wake redirection and derating strategies in a load-constrained wind farm power maximization

Abstract. Power derating and wake redirection are two wind farm control techniques proposed in the last decade as means for increasing the overall wind farm power output. While derating operations are associated with a limited gain in terms of farm energy harvesting and with a decrease in turbine loading levels, farm controls based on wake redirection proved, both in silico and experimental tests, to entail significant increases in the overall wind farm power output. However, according to wake redirection strategies, the upstream wind turbines may typically operate at large yaw misalignment angles, and the possible increase in loads that the machines may experience in such conditions represents a source of concern when it comes to testing this control on existing farms that are not specifically designed for prolonged misaligned operations. In this work, it is first demonstrated that a suitable derating level can compensate for the increase in the rotor loads associated with large misalignment angles. Secondarily, two load-constrained wind farm controls based on a combination of wake redirection and derating are proposed with the aim of maximizing the overall farm output while maintaining unaltered design load envelope of the wind turbines operating within the controlled wind farm.

Adjusting laser power to control the heat generated by nanoparticles at the site of a patient's cells.

Cancer treatment often involves heat therapy, commonly administered alongside chemotherapy and radiation therapy. The authors address the challenges posed by heat treatment methods and introduce effective control techniques. These approaches enable the precise adjustment of laser radiation over time, ensuring the tumour's core temperature attains an acceptable level with a well-defined transient response. In these control strategies, the input is the actual tumour temperature compared to the desired value, while the output governs laser radiation power. Efficient control methods are explored for regulating tumour temperature in the presence of nanoparticles and laser radiation, validated through simulations on a relevant physiological model. Initially, a Proportional-Integral-Derivative (PID) controller serves as the foundational compensator. The PID controller parameters are optimised using a combination of trial and error and the Imperialist Competitive Algorithm (ICA). ICA, known for its swift convergence and reduced computational complexity, proves instrumental in parameter determination. Furthermore, an intelligent controller based on an artificial neural network is integrated with the PID controller and compared against alternative methods. Simulation results underscore the efficacy of the combined neural network-PID controller in achieving precise temperature control. This comprehensive study illuminates promising avenues for enhancing heat therapy's effectiveness in cancer treatment.

Optimal Perioperative Pain Management of the Transgender Patient for Gender Affirming Surgery: A Scoping Review.

As we increasingly encounter transgender patients in the perioperative setting, it is important to be cognizant of appropriate medical management of the transgender patient. There is limited literature on the appropriate perioperative techniques to implement for adequate pain control in the transgender patient presenting for gender affirming procedures. In this scoping review, the authors identify publications that address perioperative pain control techniques that can be implemented by the anesthesiologist such as regional anesthesia, multimodal medications, or non-pharmacologic modalities. This scoping review included two retrospective reviews, two case reports, and one letter to the editor. There are no prospective, randomized controlled trials on this topic. The limitations of this scoping review include the limited publications that are available to analyze as this is a growing area of medicine. There are numerous variables that may play a factor in the pain experience of the transgender patient including biological factors, psychological and social factors. Techniques that are necessary for comprehensive pain management include pharmacologic, injections, physical therapy, acupuncture, massage, and more. There are limited publications on the comprehensive pain management of the transgender patient; therefore, the authors advocate that as perioperative physicians, anesthesiologists implement comprehensive preemptive analgesia techniques to avoid progression to chronic pain. Clearly more research is necessary to standardize acute pain management techniques in the transgender patient.