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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 26 Documents
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Search results for , issue "Vol 4, No 4 (2024)" : 26 Documents clear
Comparative Analysis of Path Planning Algorithms for Multi-UAV Systems in Dynamic and Cluttered Environments: A Focus on Efficiency, Smoothness, and Collision Avoidance Sukwadi, Ronald; Airlangga, Gregorius; Basuki, Widodo Widjaja; Kristian, Yoel; Rahmananta, Radyan; Sugianto, Lai Ferry; Nugroho, Oskar Ika Adi
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.v4i4.1555

Abstract

This study evaluates the performance of various path planning algorithms for multi-UAV systems in dynamic and cluttered environments, focusing on critical metrics such as path length, path smoothness, collision avoidance, and computational efficiency. We examined several algorithms, including A*, Genetic Algorithm, Modified A*, and Particle Swarm Optimization (PSO), using comprehensive simulations that reflect realistic operational conditions. Key evaluation metrics were quantified using standardized methods, ensuring the reproducibility and clarity of the findings. The A* Path Planner demonstrated efficiency by producing the shortest and smoothest paths, albeit with minor collision avoidance limitations. The Genetic Algorithm emerged as the most robust, balancing path length, smoothness, and collision avoidance, with zero violations and high feasibility. Modified A* also performed well but exhibited slightly less smooth paths. In contrast, algorithms like Cuckoo Search and Artificial Immune System faced significant performance challenges, especially in adapting to dynamic environments. Our findings highlight the superior performance of the Genetic Algorithm and Modified A* under these specific conditions. We also discuss the potential for hybrid approaches that combine the strengths of these algorithms for even better performance. This study's insights are critical for practitioners looking to optimize multi-UAV systems in challenging scenarios.
Design and Implementation of Voltage Source Inverter Using Sinusoidal Pulse Width Modulation Technique to Drive A Single-Phase Induction Motor Shneen, Salam Waley; Abdullah, Zainab B.; Dakheel, Hashmia S.
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.v4i3.1541

Abstract

A study is underway under the title, Design and implementation of voltage source inverter using sinusoidal pulse width modulation technique to drive a single-phase induction motor. The objectives of the study can be achieved by building a simulation model for a single-phase full-wave inverter consisting of four IGBT transistors. The inverter converts a direct voltage of 220 volts from the power source connected to the inverter input to an alternating voltage of 220 volts RMS. A 10-ohm resistive load is fed to the inverter output. In the first test, a square wave is generated as a result of operating the inverter in the first mode, as a result of activating two electronic switches that give the value of the voltage wave to the load, while the second mode gives the negative voltage with an interval of ten milliseconds for each mode, i.e., at a frequency of 50 Hz for twenty milliseconds for the square wave generated at the inverter output. The other model uses sinusoidal pulse width modulation technique to remove harmonics and control the inverter output by opening and closing electronic switches, which leads to removing some harmonics. The third model depends on adding a filter to obtain the basic wave and get rid of the rest of the harmonics, which results in generating a sine wave. After obtaining an inverter model that converts 220 volts direct voltage to 220 volts alternating voltage RMS as a first stage, the second stage is to feed a single-phase induction motor and operate it under test conditions that include a no-load condition, i.e., zero torque, a constant load condition, i.e., 1 Newton-meter torque, and finally a variable load condition, which is similar to many applications such as a fan, pump, etc. From the simulation results, we can say that the system is effective in operating the induction motor at the specified speed (1430 rpm) after providing the specified electrical quantities, a frequency of 50 Hz, and a voltage of 220 volts alternating voltage RMS.
Enhancing the Performance of a Wind Turbine Based DFIG Generation System Using an Effective ANFIS Control Technique Ouhssain, Said; Chojaa, Hamid; Aljarhizi, Yahya; Al Ibrahmi, Elmehdi; Maarif, Alfian; A. Mossa, Mahmoud
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.v4i4.1451

Abstract

This paper gives a look on producing energy using wind turbines and imposing robust Maximum Power Point Tracking (MPPT) technique to operate around an optimal rotational speed. A mechanical speed control based on PI controller is presented in order to extract the maximum power and optimizing the conversion efficiency of wind's kinetic energy into electric energy. A doubly-fed induction generator (DFIG) is utilized because it is preferable for applications in wind energy systems referring to the capability to regulate the output voltage and improve the stability of the grid. Its operational characteristics and the regulating procedures such as Indirect Vector Control (IVC) and other sophisticated strategies for instance the ANFIS controller enhance operating flexibility and optimum performance under diverse conditions. This has attributed the split to the improved ANFIS in that it includes the artificial neural networks besides the fuzzy logic since they improve on learning as well as parameter fine tuning. Some of them are working with a comparatively fewer number of data sets; and therefore, it can be useful in classification, modeling and control. This configuration enables to regulate the generator's magnetic flux, torque, and reactive power, adjusting to changes inside wind velocity and disruptions within the grid. The performance of the proposed MPPT-IIVC method is examined by way of simulations in Matlab/Simulink. The simulations concerned a dynamic model incorporating the wind turbine, the DFIG, and the electric grid. The results show that the proposed technique can incredibly enhance the wind energy, maintain precise regulation over speed, and effectively adjust and regulate grid voltage and frequency. The performance of the proposed ANFIS controller is compared with a PI controller and discovered that ANFIS enhances the robustness, precision, dynamic response, total harmonic distortion THD (%) of the injected current into the grid, the reference tracking ability and Overshoot (%).
Synergetic Control-Based Sea Lion Optimization Approach for Position Tracking Control of Ball and Beam System Al-Khazraji, Huthaifa; Albadri, Kareem; Almajeez, Rawaa; Humaidi, Amjad J
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.v4i4.1551

Abstract

One of the most difficult systems to control is the ball and beam (BnB) system due to its under-actuation, instability, and nonlinearity. To address these challenges, this paper presents an application of using the nonlinear synergetic control (SC) algorithm for position tracking control of the BnB system. A swarm optimization method based on sea lion optimization (SLO) has also been used to achieve an optimum dynamic performance by adjusting the suggested controller’s parameter. The Integral Time of Absolute Errors (ITAE) is employed by the SLO as an objective function to adjust the design parameters of the suggested SC. Using MATLAB software, a comparison has been made between the SC controller and the classical state feedback controller (SFC) to test the effectiveness of the suggested control algorithm. The findings illustrate that the suggested SC offers better transient response in terms of reducing the settling time and the overshoot than SFC. The effect of the external disturbance has also been examined. It has been found that SC provides more robustness performance than SFC.
Development of a Sensor-Based Glove-Controlled Mobile Robot for Firefighting and Rescue Operations Sneineh, Anees Abu; Salah, Wael A.
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.v4i4.1553

Abstract

Robots are important in preventing hazards. This paper presents the construction and testing of a mobile robot equipped with a sensor-based glove for firefighting and rescue operations. The main idea is based on the ability to control the mobile robot through the movement of a gloved hand. The glove circuit is connected to the robot circuit through Bluetooth. The MPU6050 gyroscope sensor detects the movement of a gloved hand and sends the direction of the hand’s inclination to the microcontroller, which in turn uses this information to direct the mobile robot’ movement in the desired direction. Experiments were conducted to test the mobile robot and its control system. Results showed that the robot prototype works effectively with satisfactory response to the intended direction of robot movement. An increase in safety level and a reduction in firefighting risks were also observed. The proposed robot can assist effectively in rescue operations, creating opportunities for future improvements.
Fuzzy Control for Spacecraft Orbit Transfer with Gain Perturbations and Input Constraint Nemmour, Sarah; Daaou, Bachir; Okello, Francis
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.v4i4.1549

Abstract

This paper presents the problem of fuzzy guaranteed cost tracking control for spacecraft orbit transfer with parameter uncertainties and additive controller gain perturbations and subject to input constraints, and guaranteed cost function. The goal is to perform a planar orbit transfer in a circular orbit, focusing on minimizing fuel usage while accounting for uncertainties in both the plant and controller. Spacecraft dynamics is based on the Keplerian two-body problem using polar coordinates, which allows long-distance maneuvers in circular orbit when the well-known Clohessy-Wiltshire (C-W) equation is restricted by limited-distance maneuvers. To approximate the nonlinearities in the dynamical equation of motion, a Takagi-Sugeno (T-S) fuzzy model is proposed and a linearized model is established for the output tracking problem of the orbit transfer process. Issue related to the absence of a single equilibrium point in the nonlinear system, a gain-scheduling technique based on multiple operating points is employed to develop the (T-S) fuzzy model through the fuzzy approach. Based on the parallel distributed compensation (PDC) approach, sufficient conditions for a fuzzy non-fragile guaranteed cost control are derived. Using the Lyapunov theory, the controller objectives are formulated through linear matrix inequality (LMIs) which allows the system to be transferred into a convex optimization problem. The designed controller effectively accomplishes the orbit transfer process with minimal fuel consumption and maintains the performance level below a specified upper bound. Numerical simulations are conducted to demonstrate the effectiveness of the proposed method.
Accurate Robot Navigation Using Visual Invariant Features and Dynamic Neural Fields Raoui, Younès; Elmennaoui, Nouzha
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.v4i4.1545

Abstract

Robot navigation systems are based on Simultaneous Localization and Mapping (SLAM) and obstacle avoidance. We construct maps for the robot using computer vision methods requiring high repeatability for consistent feature tracking. Also, the obstacle avoidance method needs an efficient tool for fusing data from multiple sensors. This research enhances SLAM accuracy and obstacle avoidance using advanced visual processing and dy namic neural fields (DNF). We propose two key methods: (1) an enhanced multiscale Harris detector using steerable filters for robust feature extrac tion, achieving around 90% repeatability; and (2) a dynamic neural field algorithm that predicts the optimal heading angle by integrating visual de scriptors and LIDAR data. The first method’s experimental results show that the new feature detector achieves high accuracy, outperforming exist ing methods. Its invariance to the orientation of the image makes it insen sitive to the rotations of the robot. We applied it to the monocular SLAM and remarked that the positions of the robot were computed precisely. In the second method, the results showed that the dynamic neural fields algo rithm ensures efficient obstacle avoidance by fusing the gist of the image and LIDAR data, resulting in more accurate and consistent navigation than laser-only methods. In conclusion, the study presents significant advance ments in robot navigation through robust feature detection for SLAM and effective obstacle avoidance using dynamic neural fields. These advance ments significantly enhance precision and reliability in robot navigation, paving the way for future innovations in autonomous robotic applications.
Nonlinear Model Predictive Control of a Magnetic Levitation System Using Artificial Protozoa Optimizer Noaman, Mohanad N.; Ayoub, Abdurahman Basil; Mahmood, Saif S.
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.v4i4.1668

Abstract

A magnetic levitation system (Maglev) is a sensitive, multi-parameter, nonlinear, and unstable system that is utilized to levitate a ferromagnetic object in free space. Due to its vast applications, various research studies in the field of control strategy have become extremely important and challenging. This work proposes the design of a nonlinear model predictive (NMPC) control scheme for the object position control against the nonlinearities and uncertainties of a Maglev system. A novel bio-inspired Artificial Protozoa Optimization (APO) algorithm is used to fine-tune the NMPC parameters, which include best weighting matrices ( ), shorter prediction horizons ( ), and shorter time steps ( ) to minimize the objective cost function. The effective performance of the NMPC is verified using simulation-based results in MATLAB. The CasADi toolbox is utilized to solve nonlinear optimization problems and handle the nonlinearity of the Maglev system model. Simulations are implemented for three trajectories tracking (step, sine, and square) with 20% and without Maglev parameters perturbations. To prove the superiority of the proposed controller, comparisons are made with the conventional Linear Quadratic Regulator (LQR) and proportional-integral-derivative (PID) controllers. Two performance indices are introduced, Integral of Squared Error (ISE) and Integral of Absolute Error (IAE), to examine the tracking performances of the NMPC, LQR, and PID controller.  The NMPC controller has shown more efficient performance and accurate results than other controllers. The contributions of this work include a new optimization technique of APO, a new engineering application of the APO integrated with NMPC to control a Maglev system, consideration of inherent nonlinearities and system constraints, and robustness improvement under perturbation.
Design and Quality Evaluation of the Position and Attitude Control System for 6-DOF UAV Quadcopter Using Heuristic PID Tuning Methods Mien, Trinh Luong; Tu, Tran Ngoc
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.v4i4.1594

Abstract

Nowadays, UAV quadcopters are widely used in many fields, specially in transporting the lightweight goods parcels. This article aims to design and evaluation of the quality of the 6-DOF UAV quadcopter control system using heuristic PID tuning methods to ensure stable control of flight position and attitude. Firstly, the article presents the dynamic mathematical model of the 6-DOF UAV quadcopter, including 3 Euler angle variables and 3 flight position and altitude variables. From there, the article proposes the 6-DOF UAV control syste structure with two single control loops for flight attitude, yaw angle and two dual control loops for roll-pitch angles, flight position. And then, the article presents the application of the heuristic PID tuning methods to each control loop of a 6-DOF UAV quadcopter to calculate the PID controller parameters to ensure stable control the desired flight position and altitude. The simulation results and evaluating the 6-DOF UAV quadcopter control system quality in Matlab, using the proposed heuristic PID controllers, show that the PID controllers according to the Tyreus-Luyben method gives the best quality, with a steady-state error of less than 1%. The main contribution of this article is the comparative analysis of three heuristic PID tuning methods - Ziegler-Nichols, Tyreus-Luyben, PID tuner - for controlling the position and attitude of a 6-DOF UAV quadcopter.  These findings demonstrate that the proposed PID controllers can be effectively implemented in practical UAV applications, enhancing the stability and performance of quadcopters in various fields.
Simulation and Modeling with Designing for the Proportional, Integral and Derivative Control of Industrial Robotic Arm by Using MATLAB/Simulink Shneen, Salam Waley; Juhi, Hasan H.; Najim, Hiba Ali
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.v4i4.1581

Abstract

This study aims to develop a control system for a robot arm, designed to perform precise movements along a predefined path, suitable for various industrial applications. The robot arm's movements are driven by three electric motors, each responsible for controlling a joint, enabling the arm to follow the required path accurately. To manage the complexity of multiple motors and dynamic movement requirements, an automated control system has been developed, tailored to meet the specific demands of the proposed task. A highly efficient, reliable, and safe control system design is being developed and simulated to evaluate its effectiveness in executing the required path. A simulation model is being constructed to assess the system's ability to follow the prescribed path, its responsiveness to disturbances and transient conditions, and the overall accuracy of the arm's movements. Simulation results will be analyzed to determine the system's performance across various scenarios, evaluating its adaptability to the work environment and its ability to achieve tasks with high accuracy, thereby enhancing system effectiveness.

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