Conference of Electrical, Marine and Its Application

editor celrina — 2024-11-25

CELRINA : Conference of Electrical, Marine and Its Application

TABLE OF CONTENTS

Volume 1 No. 1 November 2024

Single-Phase AC Voltage Regulator Implementation for Enhancing Transformer Efficiency in Rural Community Electrification Programs

Rahmania Firdiansya — 2024-11-25

The stability of voltage supply is a critical requirement in delivering reliable power sources, especially in rural electrification systems aimed at improving community well-being. Ensuring a constant voltage within electrical circuits is crucial, as voltage fluctuations during transmission can cause significant issues. These fluctuations, often resulting from voltage drops in distribution networks, can lead to reduced lifespan and performance of electronic devices in households and industries. Several factors influence voltage stability, including increased transmission line loading, limitations in reactive power regulation, dynamic adjustments in load-tap-changing transformers, and load characteristics. This study explores the development of a single-phase AC voltage regulator designed to enhance transformer efficiency, particularly in rural electrification programs. Using PSIM software, a voltage regulation circuit was developed, incorporating key components such as thyristors, transformers, Silicon-Controlled Rectifiers (SCRs), and other auxiliary elements. The results of this research contribute to the design of robust and sustainable electrification solutions, addressing the specific needs of underserved rural communities.

Comparing Linear Quadratic Regulator (LQR) with Proportional-Integral-Derivative (PID) Controllers for Increasing Stability in DC Motor Systems

Akhmad Azhar Firdaus — 2024-11-25

A DC motor is a versatile type of motor widely applied in industries, robotics, and household appliances due to its broad speed regulation range and ease of integration. Among the various types of DC motors, the series DC motor stands out for its high starting torque. However, this characteristic also leads to significant challenges, including overshooting during initial start-up and instability under varying load conditions. For instance, at high torque, the motor’s speed tends to decrease, while at low torque or no-load conditions, it often produces excessively high speeds. To address these issues and achieve accurate speed regulation with stable final results, a robust control strategy is required. Controllers play a pivotal role in minimizing overshoot and ensuring stability in motor performance. This research investigates the performance of two control methodologies—Proportional-Integral-Derivative (PID) and Linear Quadratic Regulator (LQR)—through MATLAB-based simulations for regulating the speed of a series DC motor. In this study, motor speed is analyzed to evaluate the effectiveness of the controllers. The simulation results reveal that both PID and LQR controllers achieve minimal error rates. However, there are notable differences in their dynamic response. The PID controller demonstrates a faster rotor speed response time compared to the LQR controller. Nonetheless, the PID controller exhibits a significant overshoot of approximately 20%, whereas the LQR controller effectively eliminates overshoot altogether. This study contributes to the growing body of knowledge in control systems engineering, particularly in evaluating advanced controllers for industrial applications.

DC Motor VD-49.15-K1-B00 Using Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT)

Rachma Prilian Eviningsih — 2024-11-25

The results of this research show that the problem of optimal control is currently attracting increasing attention, especially due to the increasing demand for high-performance systems. The concept of control system optimization influences the selection of performance indicators and techniques used to create an optimal control system. To achieve an ideal control system, rules are needed that allow decisions to be made regarding control with the aim of minimizing deviations from ideal behavior. The Linear Quadratic Regulation (LQR) method is one of the optimal control approaches for state space-based systems. The LQR controller has two parameters, namely the weight matrices Q and R, which must be determined for optimal control according to expectations, as in the case of a quadcopter or four-wing drone.

Linear Quadratic Tracking (LQT) is a control system in which the output is set to follow a predetermined path through the input. In this example, we carry out a simulation using Simulink MATLAB with an LQT circuit that can be implemented in the MATLAB application. During the course "System Optimization," the author discusses the application of methods for manufacturing DC motors with LQR and LQT settings using data sheets. The data sheet was imported into a MATLAB script and then simulated using MATLAB Simulink software to see the results step by step. The DC motor used in this research is type VD-49.15-K1-B00 which is equipped with values for moment of inertia, motor constant, damping coefficient, resistance and inductance.

Differences Between LQR and LQT Optimization Methods Regarding Output Response of Maxon EC-i 40 DC Motor

Abimanyu Manap — 2024-11-25

DC motor is an electronic component that is very common in everyday life. In general, DC motors tend to slow down under load, reduce speed, and do not run at a constant speed. The speed of a DC motor can be adjusted by changing the input voltage. Therefore, a controller is needed to keep the speed of the DC motor stable when the load changes. One method used to improve the performance of DC motors is LQR (Linear Quadratic Regulator) and LQT (Linear Quadratic Tracker). LQR aims to make the motor response close to the desired set point by reducing overshoot and undershoot in the system. LQT, on the other hand, is a linear control system that allows the system output to follow the desired reference. The LQR method produces a response that is close to the desired set point without overshoot and undershoot. Without using the LQR method, the motor response is far from the desired set point and takes a long time. Meanwhile, the LQT method speeds up the motor response to about ±0.5 seconds, but there is a little overshoot and the response has little variation. Compared to the LQR method, the LQT method is considered better because it produces a faster response to reach the set point on the Maxon EC-I 40 70 Watt DC motor.

Differential Optimization Control for MG-16B DC Motor with LQR and LQT Circuits

Rama Arya Sobhita — 2024-11-25

DC motors are an electronic component that is very often found in various daily applications. Basically, DC motors have a tendency to experience changes in speed when exposed to load, so the speed will not tend to remain constant. So that the speed of a DC motor remains stable when the load changes, a special controller is needed. One of the control methods used to improve DC motor performance is through the use of LQR (Linear Quadratic Regulator) and LQT (Linear Quadratic Tracker). LQR aims to bring the motor response closer to the desired setpoint value, as well as reducing overshoot and undershoot symptoms that can occur in the system. On the other hand, LQT is a linear control method that allows the system output to follow the desired setpoint value. The LQR method ensures that the motor response reaches setpoint without any overshoot or undershoot. Without implementing the LQR method, the motor response will be far from the desired setpoint value and it will take longer to achieve the desired motor response. By using the LQT method, the motor response is faster, in only about 0.5 seconds, but there may be slight fluctuations (ripples) in the response. Therefore, in controlling the MG-16B type DC motor, the LQT method is preferred over the LQR method because it is able to provide a faster response to reach the setpoint value.

Improving the Output Circuit System through the LQR and LQT Methods on the RS PRO 454-0883 DC Motor

Aldidymus Gregorius Senda — 2024-11-25

DC motors are components that are often found in everyday life, requiring direct voltage and current to operate. This electric motor is an electromechanical device that can convert electrical energy into mechanical energy. This paper discusses two methods, namely LQR and LQT, and considers noise, to examine the impact of noise on the system. This study uses a DC motor RS PRO 454-0883 to observe the effects of noise on the motor system. Modeling of various plant configurations, such as SISO, SIMO, MISO, and MIMO, is needed to describe the plant response graphically using software. MATLAB is used to conduct the study, including mathematical modeling of the motor to obtain the 1st and 2nd order Transfer Functions. Furthermore, simulations are carried out on each circuit for analysis. Finally, the output signals from the circuits are compared. The results show that noise has a significant impact on the 37GB500 DC motor, so an optimization method is needed to reduce noise in the motor. However, the second-order motor shows better performance compared to the first-order, as seen in the condition after the raise time

Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) control systems on M66 Series DC motors.

Rama Arya Sobhita — 2024-11-25

Some players in the industry seek to build or improve systems in their industry to produce superior products compared to their competitors. Recently, attention to optimal control problems has increased due to the increasing demand for high-performance systems. The concept of control system optimization involves the selection and design of key performance indicators that will guide the creation of an optimal control system within existing physical constraints. When designing an optimal control system, the goal is to find decision rules that will lead to control actions that minimize deviations from the desired behavior. LQR is one of the optimal control methods used in state space based systems. The LQR controller has two parameters, namely the weight matrices Q and R, which must be determined to achieve optimal control actions. LQT is an optimal control method that aims to minimize the objective function (Performance Index) and regulate the system (Plant) so that it can follow the desired reference. The step response results of the M66 Series DC motor using LQR show that the amplitude reaches around 0.799, which can be considered as 1 and reaching the setpoint. On the other hand, the step response of the LQT system produces a higher amplitude, around 0.99, which also reaches the setpoint. In addition, the LQT response has a faster rise time compared to the LQR response, around 1,509 milliseconds, and experiences an overshoot of around 1.05% and an undershoot of around 1.05%. Overall, it can be concluded that the M66 Series DC motor using LQR produces more optimal results compared to the 1st order M66 Series DC motor. This can be seen from the system's ability to use LQR to achieve setpoint, stable graphics, fast rise time, and overshoot value. and lower undershoot.

DC Motor Performance Optimization with Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) Methods

Anisa Fitri Santosa — 2024-11-25

DC motors, also known as direct current motors, are electronic devices that are commonly used in a variety of contexts, both in industrial environments and in everyday life. To ensure optimal performance of DC motors, efficient control is required. To achieve this goal, signal optimization on DC motors is carried out through the application of the Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT) methods in the control system. This study aims to analyze and compare various technical responses that have been simulated through the application of control systems. LQR and LQT were chosen as methods because they are both able to reach the optimal point and reduce errors in the device, so that the performance of the device can be adjusted to the user's preferences and produce efficient output. The object of this research is a DC motor that has a data sheet available. The advantages of DC motors include having no losses in the reactive power generated, generating considerable torque, easy to control linearly, and the ability of the controller to reduce delay time, rise time, time to reach a steady state, as well as the magnitude of surges and faults in the system. By using the DC motor data sheet, a transfer function can be built that produces the order 1 and order 2 models as the basis for implementing the four control system applications. Data collection is carried out through direct research and observation to observe the results of experiments. The results of the study are explained through narratives, tables, and diagrams.

Study on Controlled Rectifiers with Optocoupler Integration: Evaluating Impact on DC Motor Voltage Stabilization and Rotational Speed Control

Khoirun Nasikhin — 2024-11-25

This research explores a voltage regulation method for DC motor speed control using an optocoupler and a Silicon Controlled Rectifier (SCR). Traditional methods for controlling DC motor speed include varying frequency and adjusting input voltage, with voltage regulation being the most common approach. The SCR regulates the input voltage through its gate terminal, while the optocoupler provides the control signal. This study focuses on integrating optocouplers with SCRs to create an efficient controlled rectifier circuit for stable and reliable motor performance. The power circuit uses a 120V AC source to power a 190V DC motor, ensuring precise voltage stabilization and improved speed control. Through theoretical analysis and practical experimentation, the research examines the role of controlled rectifiers in motor control systems, aiming to address gaps in existing literature. The integration of optocouplers is expected to enhance system response time, stability, and motor performance. The findings offer potential improvements in DC motor control, with applications across various industrial settings where voltage regulation and speed control are essential. This study contributes a novel approach to motor control, offering valuable insights for enhancing motor stability and efficiency in engineering practices.

Design and Performance Analysis of a Controlled Single-Phase Half-Wave Rectifier Using a Single-Phase Generator for Efficient Power Conversion

Aldidimus Gregorius Senda — 2024-11-25

This research focuses on the analysis and experimental evaluation of a Single-Phase Controlled Half-Wave Rectifier integrated with a Single-Phase Generator. The primary aim of the study is to analyze and compare experimental results with theoretical calculations and simulation software outputs, thereby providing a comprehensive evaluation of the rectifier's performance. The experiments are conducted on a rectifier circuit using diode-based components, with data collected through both authentic assessment methods and direct observation of the outcomes displayed in the experimental setup. The findings of the study indicate that the inclusion of a thyristor component in the AC circuit plays a crucial role in influencing the rectifier's performance. The thyristor enables the transformation of an alternating current (AC) waveform into a direct current (DC) signal, highlighting the importance of controlled power conversion in electrical systems. The presence of the thyristor allows for the conversion of an AC-powered system into a controlled DC output, which is a significant contribution to efficient energy management in various electrical engineering applications.

37GB500-72-2463 DC Motor Analysis with Linear Quadratic Regulator Approach and Linear Quadratic Tracking

Farhan Wahyu Nur Rahman — 2024-11-25

In DC motors, it is an electrical device that consumes DC electrical power to produce mechanical torque. Because they are capable of producing relatively high torques to drive loads of the same size, DC motors are often used in a variety of applications. Permanent magnet motors, on the other hand, are linear, while DC motors are non-linear. Applications that require automatic speed control tend to have difficulty overcoming the non-linear nature of DC motors. The non-linear dynamic model of DC motors has constraints in the design of closed feedback loop control. Factors such as saturation and friction can affect the performance of conventional controls. DC motors are widely used in a variety of industries because they are able to handle applications with a wide range of power requirements, both in fixed-speed and variable-speed drives. In this paper, the analysis of the temporary speed parameters of DC motors was carried out separately using the Linear Quadratic Regulator (LQR) method. The DC motor speed of the three different motors with diverse specifications was analyzed by the LQR method. The simulation results using MATLAB software show that motors with low power applications show better and significant response with the application of the LQR method. This includes the ability to minimize deviations in speed, simple design, and reduced costs, which makes it efficient for use in controlled and controlled systems. These properties allow the speed control of DC motors to achieve the desired performance in systems with various power requirements. In addition to LQR, Linear Quadratic Tracking (LQT) is also used to control translational movements. LQT parameters are obtained through Genetic Algorithm (GA).

Development of Single-Phase AC Voltage Regulator for Renewable Energy Empowerment: Rural Generator Case Study

Latifah Anis Magfiroch — 2024-11-25

This research focuses on the development of a single-phase AC voltage controller designed using SCR TIC126, diodes, IC regulators, Op-Amp LM324N, and other essential electronic components. The module is capable of producing variable AC voltage levels based on the triggering angle of the SCR, while maintaining a fixed output frequency. The output voltage waveform is analyzed through simulation using the PSIM software and verified mathematically. The key parameter measured is the Vrms output voltage. The observed differences between simulated, and mathematical values are minimal, ensuring reliability. The triggering angles used in this study are 45°, 60°, and 90°, with a resistive load of 5 W and 100 Ω. The source voltage applied is a low AC voltage of 12.8 V at a frequency of 50 Hz. This study is contextualized within a renewable energy program aimed at empowering rural communities. By utilizing this voltage controller, the research explores its potential in enhancing the performance of small-scale generators used in off-grid areas, particularly in enabling stable and efficient electricity supply for households and community facilities. The findings highlight the module’s applicability in community empowerment programs, offering a practical and scalable solution for improving energy access in underserved regions.

System Optimization Study on IG-22GM DC Motor Plant with LQR and LQT Analysis Approach

Aditya Achmad Safriansyah — 2024-11-25

A control system, or commonly known as a control system, is a device used to monitor, instruct, and manage the condition of a system. A DC motor, on the other hand, is a device that continuously converts electrical energy into kinetic energy or mechanical motion. DC motors have two terminals, namely the positive terminal and the negative terminal, which require voltage in order to operate. The use of DC motors is very common in a variety of modern industrial systems, with various specifications tailored to the needs of specific industries. One of the main reasons why DC motors are a top choice in modern industry is due to their ability to regulate rotational speeds over a wide range, thanks to the wide variety of speed control methods that can be applied. One common method used to regulate the speed of a DC motor is to use a speed control device, which allows the speed adjustment according to the needs of the device's working system. Therefore, experiments are needed to optimize the operation of DC motors through mathematical modeling and control systems using Matlab software. In the context of this problem, the two optimization methods used in this system are Linear Quadratic Regulation (LQR) and Linear Quadratic Tracking (LQT) to ensure optimal system operation. Therefore, in this study, we modeled and simulated an upgraded DC motor with optimized and non-optimized circuits.

Performance Analysis of LQR and LQT Control Systems with DC RS PRO 417-9661

Anggara Trisna Nugraha — 2024-11-25

Technology is intended to improve human work efficiency, but technology performance can be affected by various factors, including environmental factors, controller configuration with computers, and characteristics of the technology itself, often referred to as interference. This interference can result in the technology not operating optimally. Therefore, it is necessary to optimize the system to reduce interference. This research was carried out to evaluate the impact of interference on the system, using a DC motor model 417-9661 as a study object. DC motor systems are utilized in a variety of configurations involving various inputs and outputs. In this context, two variables are also introduced, namely order 1 and order 2. This research process involves the use of Matrix Laboratory (MATLAB) software and involves several stages. First, there is the mathematical modeling stage of the motor to obtain the first-order and second-order transfer function values. Second, a simulation is carried out on each configuration to be analyzed. Finally, a comparison of the signal output results from each configuration was carried out. The research results show that interference has a very high impact on the 417-9661 DC motor. Therefore, an optimization method is needed to reduce interference with the motor. Furthermore, second-order motorbikes show superior performance compared to first-order motorbikes, especially seen from the riding time conditions.

Optimization of LQR and LQT Control System Performance on RS PRO 834-7641 DC Motor with and Without Disturbance

Zukhruf Zidane Handandi — 2024-11-25

DC motors are the most commonly used type of motor compared to other electric motors. The advantages of this motor include simple, sturdy construction, relatively cheap price, and require uncomplicated maintenance. However, the main focus in this discussion is to keep the motor speed constant. When there is a change in the load on the DC motor with a certain value of the nominal load, its response can change even though the controller has been given. To overcome this problem, the optimal control techniques used are Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT). In this study, the author uses a closed-loop control system to understand how the RS PRO 834-7641 type DC motor responds with mathematical modeling of order 1 and order 2 when integrated into a system. Furthermore, simulations are carried out using MATLAB Simulink software to analyze the risetime, overshoot, undershoot responses under normal conditions, and when there is noise in the system. This study requires a DC motor with a terminal inductance phase to phase and terminal resistance phase to phase values, which are used to create mathematical modeling of speed and current sensors as feedback functions in a system with dual outputs. The LQR controller has two parameters, namely the Q and R weight matrices, which must be determined to produce optimal control actions as expected. Examples of implementation of the LQR and LQT methods include speed control of induction motors, frequency control in generator power plants, to quadcopter drones. The combination of the LQR and LQT methods with the discipline of system optimization is very important to achieve optimal points and reduce errors in a device, so that device performance can be adjusted according to user wishes.

Output Response with LQR and LQT Methods on RS PRO 834-7641 DC Motor for Optimization. Elmi Hidayana

Elmi Hidayana — 2024-11-25

Technological developments occur very quickly, and in the manufacturing process, various methods are applied by each developer. One method commonly used in technology creation is system optimization. System optimization is an approach used to achieve the best results on a particular technology. There are various methods for system optimization, such as SISO, MISO, SIMO, MIMO, and Noise. In this context, we will explore system optimization using SISO, MISO, SIMO, and MIMO circuits using the RS PRO 834-7641 DC Motor as a plant. The RS PRO 834-7641 DC motor is one of the plants that is easily accessible in the control system. The LQR optimal control method, which is state space based, is used in this system. The LQR controller has two main parameters, namely the weight matrices Q and R, which must be determined to create optimal control actions. In addition, the Linear-Quadratic Tracker (LQT) method is used as the main solution for tracking problems in linear systems. LQT is designed to design optimal control so that a linear control system can track a preset reference trajectory.

Design and Simulation of DC Motor Control Based on LQR and LQT for Optimal Control System

Lugas Jagad Satrianata — 2024-11-25

This paper explains the system identification process in the context of using a DC motor. DC motors are one of the most common types of electric motors used in various industrial applications. This is due to the various advantages of DC motors, such as their simple structure, robustness, relatively affordable cost, and no complicated process in their operation. However, the main challenge discussed in this article is maintaining a constant motor speed, especially when there is a certain load change. Load changes can cause changes in motor response, even if a controller has been implemented. To overcome this, the optimization control techniques used are Linear Quadratic Regulator (LQR) and Linear Quadratic Tracking (LQT). In this study, a DC Motor System Identification Module was developed with Arduino, which aims to facilitate the acquisition of DC motor models using first-order and second-order modeling methods. This module integrates Arduino and Simulink Matlab, which is used to collect input and output data needed in the system identification process. The result of this system identification is a DC motor model with an exogenous quadratic autoregressive (ARX) model. In addition, in the implementation of the LQR control technique, the parameter of the Q element matrix is generated by multiplying the system matrix C by the system matrix C. While the R element matrix is adjusted to the actual test of 0.0001. The experimental results show that the use of LQR control produces a more optimal system response time constant.

Analysis of Thyristor Usage in Controlled Half-Wave Rectifiers on DC Motor Speed Control

Anggara Trisna Nugraha — 2024-11-25

Speed control of a motor can be achieved in several ways, one of which is by varying the armature voltage (Vt) supplied to the motor. A DC motor operates with the aid of a rectifier circuit to convert AC signals into DC. The controlled half-wave rectifier circuit is one of the simplest forms of rectifier circuits, as it requires fewer components and provides an adjustable output voltage through changes in the firing angle of the thyristor. This makes the circuit suitable for controlling the speed of a DC motor. A simulation in PSIM software was selected to investigate the relationship between the thyristor firing angle in the controlled half-wave rectifier circuit and the speed of a series DC motor. The simulation was conducted by varying the thyristor firing angle at 0°, 15°, 30°, 45°, 60°, 90°, 120°, and 150° to observe the effects on the speed of the series DC motor. Additionally, different torque loads, including 0 Nm, 0.5 Nm, and 1 Nm, were applied to assess the impact on motor speed. The results showed that increasing the thyristor firing angle leads to a decrease in motor speed due to the reduction in armature voltage. Similarly, higher torque loads resulted in lower motor speed. Motor speed increased with higher source voltage and firing angle if a full-wave rectifier was used, as it provides a higher output voltage compared to a half-wave rectifier.

Mathematical modeling and simulation of open loop and closed loop systems for a second-order Rotary type S-50-39 motor: Ziegler Nichols

Moses Yudha Dua Lembang — 2024-11-25

This study examines optimal control methods for a servo motor, focusing on performance
evaluation in both open-loop and closed-loop conditions. In open-loop configuration, the PID
method is identified as the best solution due to its ability to provide superior system stability and
response. For closed-loop systems, a proportional (P) control method is selected based on its fast
rise time and very small overshoot, making it suitable for applications requiring rapid response and
high accuracy. The parameter values for the closed-loop system are determined using the RouthHurwitz criteria to ensure system stability. The findings of this research provide practical guidance
for the efficient and stable implementation of DC motor control.

DC Motor Analysis 42D29Y401 for System Optimization through LQR and LQT Approaches

Yulian Fatkur Rohman — 2024-11-25

DC motors are one of the control systems used to control, manage, and control the condition of a system. Especially in DC motors it is used to convert direct current (DC) into kinetic energy. This DC motor has two poles, namely positive (+) and negative (-) poles that function so that they can be active. DC motors have the advantage of being easy to regulate speed in a wide range with various methods used which makes this DC Motor widely used in Industry, especially Modern Industry. Not specifically in a Modern Industry, but various kinds of Modern Industries use this DC Motor with various variations depending on the needs and needs of the industry. One of the methods that can be used to adjust the speed of the DC Motor and to suit the needs of the tool working system is to use a speed control device. Thus, the performance optimization experiment of DC Motors can be carried out using mathematical modeling and control systems supported by Software. One of the software that can be used and is in accordance with the experiment is the Matlab software. The optimization system methods used for the optimal occurrence of a system in this problem are LQR (Linear Quadratic Regulator) and LQT (Linear Quadratic Tracking). Thus, in this study, the representation and simulation of DC motors with and without a series of optimizations are carried out.