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Alfian Ma'arif
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International Journal of Robotics and Control Systems
Published by Association for Scientific Computing Electronics and Engineering
ISSN : -     EISSN : 27752658     DOI : https://doi.org/10.31763/ijrcs
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
International Journal of Robotics and Control Systems is open access and peer-reviewed international journal that invited academicians (students and lecturers), researchers, scientists, and engineers to exchange and disseminate their work, development, and contribution in the area of robotics and control technology systems experts. Its scope includes Industrial Robots, Humanoid Robot, Flying Robot, Mobile Robot, Proportional-Integral-Derivative (PID) Controller, Feedback Control, Linear Control (Compensator, State Feedback, Servo State Feedback, Observer, etc.), Nonlinear Control (Feedback Linearization, Sliding Mode Controller, Backstepping, etc.), Robust Control, Adaptive Control (Model Reference Adaptive Control, etc.), Geometry Control, Intelligent Control (Fuzzy Logic Controller (FLC), Neural Network Control), Power Electronic Control, Artificial Intelligence, Embedded Systems, Internet of Things (IoT) in Control and Robot, Network Control System, Controller Optimization (Linear Quadratic Regulator (LQR), Coefficient Diagram Method, Metaheuristic Algorithm, etc.), Modelling and Identification System.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 361 Documents
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Lightning Risk Assessment, Control and Protection Scheme Design for a Rooftop Photovoltaic System in the New Capital of Egypt Omar, Ahmed I.; Abd-Allah, M. A.; Shokry, Ahmed; Said, Abdelrahman
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1525

Abstract

The absence of an effective lightning protection system for photovoltaic (PV) systems can hinder their integration into networks. Outdoor PV installations are vulnerable to direct or indirect lightning strikes, resulting in damaging overvoltages that harm the PV structure. These systems, often situated on rooftops or open fields, face increased lightning strike risks due to their exposure compared to more sheltered setups. Lightning-induced surges can harm sensitive electrical components like panels, inverters, and wiring, leading to potential damage and downtime. The complexity of PV systems, with interconnected components, makes designing protection strategies challenging. Compliance with lightning protection standards is crucial to prevent damage, downtime, and financial losses. Implementing effective protection measures involves grounding, surge protection, and adherence to regulations. Lightning protection systems intercept strikes and safely direct electrical energy to the ground, safeguarding sensitive components and ensuring continuous power generation. The IEC 62305-2 standard guides lightning risk assessment and mitigation, aiding in evaluating risks, calculating damage likelihood, and designing protective measures. A case study focusing on the Arab African International Bank's rooftop PV system in Egypt illustrates the importance of lightning risk management in financial, operational, and regulatory contexts for solar projects. Risk assessment aims to identify vulnerabilities, implement mitigation strategies, and ensure safe, reliable system operation. By addressing lightning risks effectively, stakeholders can enhance system safety, reliability, and longevity while minimizing downtime and revenue loss associated with lightning strikes.
Optimizing Aircraft Pitch Control Systems: A Novel Approach Integrating Artificial Rabbits Optimizer with PID-F Controller Abualigah, Laith; Izci, Davut; Ekinci, Serdar; Zitar, Raed Abu
International Journal of Robotics and Control Systems Vol 4, No 1 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i1.1347

Abstract

The precise control of aircraft pitch angles is critical in aviation for maintaining specific attitudes during flight, including straight and level flight, ascents, and descents. Traditional control strategies face challenges due to the non-linear and uncertain dynamics of flight. To address these issues, this study introduces a novel approach employing the artificial rabbits optimizer (ARO) for tuning a PID controller with a filtering mechanism (PID-F) in aircraft pitch control systems. This combination aims to enhance the stability and performance of the aircraft pitch control system by effectively mitigating the kick effect through the incorporation of a filter coefficient in the derivative gain. The study employs a time-domain-based objective function to guide the optimization process. Simulation results validate the stability and consistency of the proposed ARO/PID-F approach. Comparative analysis with various optimization algorithm-based controllers from the literature demonstrates the effectiveness of the proposed technique. Specifically, the ARO/PID-F controller exhibits a rapid response, zero overshoot, minimal settling time, and precise control during critical phases. The obtained results position the proposed methodology as a promising and innovative solution for optimizing aircraft pitch control systems, offering improved performance and reliability.
A Systematic Review of the Use of Technology in Educational Assessment Practices: Lesson Learned and Direction for Future Studies Retnawati, Heri; Kardanova, Elena; Sumaryanto, Sumaryanto; Prasojo, Lantip Diat; Jailani, Jailani; Arliani, Elly; Hidayati, Kana; Susanti, Mathilda; Lestari, Himmawati Puji; Apino, Ezi; Rafi, Ibnu; Rosyada, Munaya Nikma; Tuanaya, Rugaya; Dewanti, Septinda Rima; Sotlikova, Rimajon; Kassymova, Gulzhaina Kuralbayevna
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1572

Abstract

Previous studies have demonstrated that technology helps achieve learning outcomes. However, many studies focus on just one aspect of technology’s role in educational assessment practices, leaving a gap in studies that examine how various aspects affect the use of technology in assessments. Hence, through a systematic work, we analyzed the extent and manner in which technology is integrated into educational assessments and how education level, domain of learning, and region may affect the use of technology. We reviewed empirical studies from two major databases (i.e., Scopus and ERIC) and a national journal whose focus and scope are on educational measurement and assessment, following PRISMA guidelines for systematic reviews. The findings of the present study are directed towards emphasizing the roles of technology in educational assessment practices and how these roles are adapted to varying educational contexts such as the level of education, the three domains of learning (i.e., cognitive, psychomotor, and affective), and the setting in which the assessment was conducted. These findings not only highlight the current roles of technology in educational assessment but also provide a roadmap for future research aimed at optimizing the integration of technology across diverse educational contexts.
Performance Enhancement of DC Motor Drive Systems Using Genetic Algorithm-Optimized PID Controller for Improved Transient Response and Stability Aziz, Ghada Adel; Abdullah, Fatin Nabeel; Shneen, Salam Waley
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1602

Abstract

Some systems require mechanical power, which can be used in many applications, including rotating vehicle wheels, pulling elevators, and moving robot limbs, etc. Mechanical or kinetic energy can be produced and generated from electrical machines, which can be represented by an electric motor, which is a machine that operates on electrical energy, i.e. input energy, and produces mechanical energy, i.e. output energy. One of the most common and widely used motors is the DC motor, which has features that make it a matter of interest to researchers, producing and manufacturing companies to develop and improve its performance. The motor is characterized by flexibility, low cost, durability, and the ability to control the speed and position of the rotating member using traditional, expert and intelligent control systems to achieve appropriate performance according to the field of application. In linear systems, traditional systems (Proportional-Integral-Derivative Controller (PID) have succeeded, while their performance is weak and unacceptable in nonlinear systems. Therefore, expert and intelligent control systems are relied upon to improve the performance of electric motors. It is proposed to implement and operate an electric motor control system using the genetic algorithm to verify its effectiveness in improving performance compared to the traditional one (PID). The genetic algorithm was chosen to address the optimization challenges because it is commonly used in artificial intelligence applications in various fields that are suitable for real time. Therefore, this study presented improving the performance of the traditional controller using the genetic algorithm. Through comparison, the possibility of improving the system performance with changing operating conditions was verified by adjusting the parameters of the traditional controller. The simulation was performed using Matlab, and the DC motor specifications included a rated voltage of 32.4 V, a rated current of 2 A, a rated speed of 536 rad/s, and a power of 54 watts. The conventional controller is responsible for the basic feedback control, while the GA-PID controller optimizes the control parameters to improve the system performance.
Prognostic Real Time Analysis of Induction Motor Kumar, C. S. Subash; Ravikrishna, S.; Rajasekar, P.; Venkatesan, Mani
International Journal of Robotics and Control Systems Vol 4, No 1 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i1.1252

Abstract

Variable speed induction motors controlled by variable frequency drives are used for a variety of industrial applications. Monitoring and prognostic occurrence of faults in induction motors is vital for reducing the downtime and accidents. The proposed work focuses on failures in induction motors owing to bearing misalignment and insulation failure in the stator that results in abnormal vibration and temperature rise in the motor. This research intends to improve the dependability and safety of industrial operations by identifying faults in their early stages using advanced methods such as vibration analysis and thermal monitoring. This work focuses on fault prognosis in induction motor through vibration data, which is analyzed using Daubechies orthogonal db10 wavelet transformation. The neural network algorithm optimizes the analyzed results to enable real time fault detection. The temperature of the stator is measured to estimate the expected lifetime of the insulator. The real time vibration and temperature data is measured and transferred to prognostic model build in MATLAB using ATMEGA 32 controller and the results are validated for good, allowable and not permissible conditions of motor based on ISO 10816 vibration levels for Class I motors. The improved accuracy and efficiency of real-time fault detection have the potential to reshape maintenance strategies and enhance the overall reliability of variable speed induction motors.
Performance of New Control Strategy of Dual Stator Induction Generator System Applied in Wind Power Generation Ameur, Fatima; Kouzi, Katia; Ameur, Khadidja
International Journal of Robotics and Control Systems Vol 4, No 2 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i2.1404

Abstract

In order to improve the quality of energy and reduce the harmonics produced by the power electronics converters, it is proposed and developed in this article the direct torque control, in which the flux and torque are estimated from the only measurable electrical quantities. The direct torque control DTC method, to enhance the dynamic and static performances as well as the robustness of the control of the Wind Energy Conversion System (DSIG). DTC is a control technique that exploits the possibility of imposing torque and flux on alternating current machines in a decoupled manner, once powered by a voltage inverter without current regulation made by a feedback loop, ensuring a decoupling, similar to that obtained from a vector control. The technique involved rapid torque response, insensitivity to parametric variation, in particular the machine's rotor time constant and systematic suitability for control without speed sensor. The main function of the generator side controller is to track the maximum power through controlling the rotational speed of the wind turbine using PI controller. The performance and the effectiveness of the   proposed control system are tested via simulation results in terms of reference tracking, and robustness against parameters variations of the DSIG. Simulation results for 1.5 MW DSIG control show robust with respect to the parametric variation 2 Rs, 1,5 Rs et 0.5 Rs, and fast dynamic behavior of system, with the temps of response is 0.02 s, active power extracted 0.15 MW with lambda 9 and Cp 0,5 that the wind turbine can operate at its optimum power point for a wide range of wind speed and power quality can be greatly improved.
Optimizing Low-Voltage Ride-Through in DFIG Wind Turbines via QPQC-Based Predictive Control for Grid Compliance Badawi, Ahmed; Soliman, Mostafa; Elzein, I. M.; Alqaisi, Walid
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1661

Abstract

This paper introduces a novel Model Predictive Control (MPC)-based strategy to enhance Low-Voltage Ride-Through (LVRT) capability for wind turbines equipped with Doubly Fed Induction Generators (DFIGs). According to modern grid codes, grid-connected wind turbines must remain operational during voltage dips and support the grid by injecting both active and reactive power. However, voltage dips pose significant challenges for (DFIG)-based wind turbines because voltage dips can induce significant large inrush current in the rotor, potentially damaging the rotor converter. Conventional control methods employ proportional-integral (PI) controllers for rotor current regulation and crowbar circuits to protect the converter by diverting high rotor currents away from the converter when they exceed their safe limit. While effective in protecting the hardware, crowbar activation temporarily disconnects the rotor from control, leading to a loss of power injection capabilities and noncompliance with grid codes. To overcome these limitations, this paper proposes an MPC-based rotor current controller formulated as a Quadratically-Constrained Quadratic Programming (QCQP) optimization problem. This controller explicitly incorporates rotor current and voltage constraints while optimizing control performance during grid faults. MATLAB-based simulations for both low- and medium-voltage dips demonstrate the superiority of the proposed approach over conventional PI controllers. The results confirm that the MPC strategy ensures LVRT compliance without the need for a crowbar circuit, maintaining stability and improving performance during a wide-range of fault conditions.
Comparative Electromagnetic Performance Analysis of Double Stator and Single Stator Superconducting Generators for Direct-Drive Wind Turbines Elhindi, Mohamed; Abdalla, Modawy Adam Ali; Omar, Abdalwahab; Pranolo, Andri; Mirghani, Abdelhameed; Omer, Abduelrahman Adam
International Journal of Robotics and Control Systems Vol 4, No 2 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i2.1385

Abstract

Superconducting synchronous generators, especially for 10-MW direct-drive wind power systems, are gaining prominence due to their lightweight, compact design, lowering energy generation costs compared to conventional generators. With the ability to generate high magnetic fields. various approaches are exist for designing such generators for example modular superconducting generators which allow for easier assembly, maintenance, and scalability by dividing the generator into smaller, interchangeable components and single stator which simplifying the generator's design and reducing manufacturing costs. This study introduces a novel concept of a double-stator superconducting generator alongside a conventional single-stator superconducting generator, aiming to investigate and contrast the electromagnetic performance of both machine types considering different number pole pairs. Booth of the machines has been designed and studied applying 2d finite element model (COMSOL Multiphysics). The compared machine parameters include: the flux linkage and electromagnetic torque. Our study and compression of the two machines reveal that the double stator superconducting generator is characterized by high electromagnetic torque compared to its single-stator counterpart. the analysis also reveals that increasing the pole pairs number leads to high electromagnetic torque and higher magnetic flux density.
NMPC Based-Trajectory Tracking and Obstacle Avoidance for Mobile Robots Qasim, Mohammed Salim; Ayoub, Abdurahman Basil; Abdulla, Abdulla Ibrahim
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1605

Abstract

This paper presents the design of a Nonlinear Model Predictive Controller (NMPC) for a wheeled Omnidirectional Mobile Robot (OMR) in order to track a desired trajectory in the presence of previously unknown static and dynamic obstacles in the environment around the robot. A laser rangefinder sensor is used to detect the obstacles where each obstacle occupies numerous points of every sensor reading. The points that belong to each obstacle are then clustered together using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. This research introduces a novel approach to represent obstacles as multiple rotated ellipses, enabling a more accurate representation of complex obstacle shapes without overestimating their boundaries, thereby allowing the robot to navigate through narrow passages. CoppeliaSim robotic simulator is utilized to create the virtual simulation environment as well as simulate the OMR dynamics. MATLAB with the help of the CasADi toolbox is used for the process of the laser rangefinder readings and the implementation of NMPC, respectively.  To validate the effectiveness and robustness of the proposed approach, three simulation scenarios are conducted, each involving distinct trajectories and varying densities of static and/or dynamic obstacles. The proposed control architecture exhibits remarkable performance, enabling the OMR to effectively navigate through narrow passages and avoid multiple static and dynamic obstacles while closely adhering to the desired trajectory.
A New Hybrid Intelligent Fractional Order Proportional Double Derivative + Integral (FOPDD+I) Controller with ANFIS Simulated on Automatic Voltage Regulator System Mohammed, Abdullah Fadhil; Marhoon, Hamzah M.; Basil, Noorulden; Ma'arif, Alfian
International Journal of Robotics and Control Systems Vol 4, No 2 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i2.1336

Abstract

In the dynamic realm of Automatic Voltage Regulation (AVR), the pursuit of robust transient response, adaptability, and stability drives researchers to explore novel avenues. This study introduces a groundbreaking approach—the Hybrid Intelligent Fractional Order Proportional Derivative2+Integral (FOPDD+I) controller—leveraging the power of the Adaptive Neuro-Fuzzy Inference System (ANFIS). The novelty lies in the comparative analysis of three scenarios: the AVR system without a controller, with a traditional PID controller, and with the proposed FOPDD+I-based ANFIS. By fusing ANFIS with a hybrid controller, we forge a unique path toward optimized AVR performance. The hybrid controller, based on FOPID (Fractional Order Proportional Integral Derivative) principles, synergizes individual integral factors with ANFIS, augmenting them with a doubled derivative factor. The ANFIS design employs a hybrid optimization learning scheme to fine-tune the Fuzzy Inference System (FIS) parameters governing the AVR system. To train the fuzzy inference system, we utilize a Proportional-Integral-Derivative (PID) simulation of the entire AVR system, capturing essential data over approximately seven seconds. Our simulations, conducted in MATLAB/Simulink, reveal impressive performance metrics for the FOPDD+I-ANFIS approach: Rise time: 1.1162 seconds, settling time: 0.5531 seconds, Overshoot: 0%, Steady-state error: 0.00272, These results position our novel approach favorably against existing works, underscoring the transformative potential of intelligent creation in AVR control.

Page 25 of 37 | Total Record : 361

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