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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 3 (2024)" : 26 Documents clear
Design of Novel STASOSM Controller for FOC Control of Dual Star Induction Motor Drives Pham, Ngoc Thuy
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1443

Abstract

In this paper, a Novel Super-Twisting Algorithm combined with Improved Second - Order Sliding Mode (NSTASOSM) for the Field-Oriented Control (FOC) of high performance SPIM drives is proposed. This structure, on the one hand, effectively solves the weaknesses of traditional backstepping control (BS) and sliding mode (SM) control that are the dependent on the change of parameters, load disturbance and the phenomenon of chattering, on the other hand, increases the convergence speed and the reference tracking ability, enhance the robust and stably of drive systems even when working in conditions of uncertain parameter and load disturbances, eliminates the chattering phenomenon. The obtained results by simulation using the Matlab/ Simulink tool verified the performance of this proposed control structure.
Arduino-Controlled Multi-Function Robot with Bluetooth and nRF24L01+ Communication Ahmmed, Faysal; Rahman, Asef; Islam, Amirul; Alaly, Ajmy; Mehnaj, Samanta; Saha, Prottoy; Hossain, Tamim
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1517

Abstract

This paper outlines the design and development of an advanced robotic system that integrates hardware implementation with theoretical simulation to address the need for versatile and user-friendly robotic solutions in various environments. Addressing the issue of limited adaptability in existing robotic systems, we propose a wireless, voice and gesture-controlled robot car with an integrated robotic arm capable of performing complex tasks such as line following, obstacle avoidance, object manipulation, and autonomous navigation over one-kilometer range. To improve operational efficiency and user involvement, this paper designs a multifunctional robotic platform that integrates user-friendly control interfaces with inexpensive, state-of-the-art sensor technologies. To achieve this, we integrate a variety of sensors, including ultrasonic sensors for precise distance measurement, infrared sensors for object detection and line following, an L298 motor driver for controlling geared motors, servo motors for controlling robotic arms, a flex sensor for claw control, and an mpu6050 accelerometer for gesture recognition. The system also uses a custom-made Bluetooth app for remote control, nRF24L01+ for long-range wireless control, and Arduino Mega and Nano for processing and control functions. The results demonstrate the robot functions well in dynamic conditions, and it can be used in hospitals to assist healthcare professionals, in restaurants for food delivery, and in industrial settings for object manipulation. The system’s design proves robust in real-world scenarios, offering significant improvements in accessibility and operational efficiency. This study aligns with Sustainable Development Goals (SDGs) 3 (Good Health and Well-being), 9 (Industry, Innovation, and Infrastructure), and 17 (Partnerships for the Goals). The robotic arm's potential application in healthcare settings advances SDG 3, its contribution to industrial productivity advances SDG 9, and collaborations with tech companies to expand and improve the robot's capabilities promote SDG 17.
A Novel Predictive Voltage Control Technique for a Grid Connected Five Phase Permanent Magnet Synchronous Generator Mahmoud, Hussein; A. Mohamed, Mohamed; A. Hassan, Ahmed; A. Mossa, Mahmoud
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1386

Abstract

This study focuses on developing an effective control strategy to enhance the dynamics of a wind turbine grid-connected five-phase permanent magnet synchronous generator (PMSG). To visualize the superior performance of the newly proposed controller, the generator's performance is evaluated with another traditional predictive control scheme: predictive torque control (PTC). However, the vector control principle is applied to the GSC converter. The PTC has limitations such as significant ripple, substantial load commutation, and the inclusion of a weighting element in its cost functions. The proposed predictive methodology aims to overcome limitations, uses a simple cost function, and doesn't require weighting elements to address concerns about stability errors. Comparing the proposed predictive voltage controller (PVC) to the PTC, the findings show that the suggested PVC has many benefits, including faster dynamic response, a simpler control structure, fewer ripples, reduced current harmonics, low computation burdens, and robustness, so the generated power affects system efficiency, leading to improved power quality and reduced switching losses, enhancing power converters efficiency and their switches lifespan, this fact is verified mathematically as the total harmonic distortion (THD) has reduced to 1.346% average percentage for the proposed controller. However, the THD of the PTC is 3.05%. In addition, the study examines the incorporation of pitch angle control (PAC) and maximum power point tracking (MPPT). These controls restrict the consumption of wind energy when the generator speed surpasses its rated speed and optimize the extraction of wind energy during periods of low wind availability. In summary, the proposed PVC-enhanced control system reveals superior performance in dynamic response, control simplicity, current quality, and computational efficiency compared to other methods.
Impact of Smart Greenhouse Using IoT for Enhanced Quality of Plant Growth Ali, Munawar; Gunawan, Anak Agung Ngurah; Prasetya, Dwi Arman; Ibrahim, Mohd Zamri Bin; Diyasa, I Gede Susrama Mas
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1277

Abstract

Greenhouses play a crucial role in manipulating environmental conditions for optimal plant growth. While existing greenhouses enhance control over environmental factors, manual controls such as watering and humidity regulation often lead to suboptimal production and increased costs. This study proposes the development of a smart greenhouse with an automatic control system using fuzzy logic, specifically fuzzy Sugeno, to regulate watering and lighting based on soil moisture, temperature, and light intensity. The system's architecture involves sensor inputs, microcontroller processing, and the activation of actuators, such as UV lights and water pumps. Fuzzy logic is applied to interpret soil moisture and temperature inputs and determine optimal irrigation durations. The system's functionality is tested and validated through functional testing, Blynk application testing, and fuzzy Sugeno testing. Results indicate the successful implementation of the proposed smart greenhouse system. Functional testing demonstrates accurate sensor readings, including temperature and soil moisture. The Blynk application enables real-time monitoring and control of environmental conditions. Fuzzy Sugeno testing validates the irrigation control system, with an average error rate of 1.3%, affirming the system's alignment with desired specifications. Plant testing in different conditions showcases the effectiveness of the smart greenhouse in supporting plant growth and development.
Honey Badger Algorithm Based DVR Controllers for Improved Power Quality‏ in a Microgrid Combined of (Wind System\ Grid\Nonlinear Load) Zidan, Ahmed Atef; Ibrahim, Ahmed M.; Omar, Ahmed I.
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1494

Abstract

Power quality (PQ) is crucial in today's energy supply networks, where even little voltage fluctuations can have a big impact on how well household appliances and technologies operate. The suggested dynamic voltage regulator (DVR) approach helps to create a new generation power grid that is more dependable and effective. In this study, the honey badger optimizer (HBO) is used to optimize the controllers of the DVR for improving PQ via voltage control. The efficacy of the optimized DVR is further increased by its integration with a microgrid (MG) wind supply. The suggested technique makes use of a low-complexity control approach for voltage regulation to adjust for harmonic distortion, swells, and voltage dips in the addressed system. The technique accomplishes voltage improvement, bus stabilization, energy-efficient utilization, and harmonic distortion reduction by using the DVR in conjunction with an MG wind supply. Various voltage disturbances, such as balanced and unbalanced swell and sag, voltage imbalance, notching, various fault states, and power system harmonic distortion, are taken into consideration to show the approach's usefulness. The findings indicate PQ enhancement, demonstrating that the load voltage roughly matches the nominal value.
Applications of Multi-Objective OPF Solutions with Optimal Placement of Multiple and Multi-Type FACTS Units to IEEE System: Comparison of Different Approaches Hakmi, Sultan Hassan
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1472

Abstract

Optimal power flow (OPF) problem and its implications for power system stability and efficiency is investigated in this study. OPF, a restricted optimization query with non-linearity and non-convexity, is one of the most challenging and fascinating problems in the recent power system. Based on these parameters, researchers have been working hard over the past few decades to identify the best solutions to the OPF issue that maintain system stability. This work presents multi-objective OPF solutions utilizing Newton's technique with numerous multi-type FACTS units. First, the GA is applied to identify the perfect size and location of the FACTS units. Next, the generator and FACTS settings are optimized. In this instance, four scenarios are taken into consideration and three OFs are employed to see how the OFs affect the positioning and dimensions of FACTS devices. The OF is suggested to consider the reduction of both generation costs and transmission losses while also optimizing the power transfer capacity of designated corridors. A full analysis relating to the IEEE-30 bus system is presented and analyzed.
Capability of Hybrid Long Short-Term Memory in Stock Price Prediction: A Comprehensive Literature Review Furizal, Furizal; Ma'arif, Alfian; Firdaus, Asno Azzawagama; Suwarno, Iswanto
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1489

Abstract

Stocks are financial instruments representing ownership in a company. They provide holders with rights to a portion of the company's assets and earnings. The stock market serves as a means for companies to raise capital. By selling shares to the public, companies can obtain funds needed for expansion, research and development, as well as various other investments. Though significant, predicting stock prices poses a challenge for investors due to their unpredictable nature. Stock price prediction is also an intriguing topic in finance and economics due to its potential for significant financial gains. However, manually predicting stock prices is complex and requires in-depth analysis of various factors influencing stock price movements. Moreover, human limitations in processing and interpreting information quickly can lead to prediction errors, while psychological factors such as bias and emotion can also affect investment decisions, reducing prediction objectivity and accuracy. Therefore, machine processing methods become an alternative to expedite and reduce errors in processing large amounts of data. This study attempts to review one of the commonly used prediction algorithms in time series forecasting, namely hybrid LSTM. This approach combines the LSTM model with other methods such as optimization algorithms, statistical techniques, or feature processing to enhance the accuracy of stock price prediction. The results of this literature review indicate that the hybrid LSTM method in stock price prediction shows promise in improving prediction accuracy. The use of optimization algorithms such as GA, AGA, and APSO has successfully produced models with low RMSE values, indicating minimal prediction errors. However, some methods such as LSTM-EMD and LSTM-RNN-LSTM still require further development to improve their performance.
Simulation and Arduino Hardware Implementation of ACO, PSO, and FPA Optimization Algorithms for Speed Control of a DC Motor Najem, Adil; Moutabir, Ahmed; Ouchatti, Abderrahmane
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1483

Abstract

This article proposes implementing and comparing the effectiveness of three optimization algorithms (ACO, PSO, and FPA) for tuning a proportional-integral-derivative (PID) controller on an Arduino Mega 2560 board. This relatively unexplored approach aims to evaluate these algorithms through practical experiments. The choice of PID control is due to its design simplicity and widespread industrial use. Similarly, the permanent magnet DC motor (PMDC) was selected because of its crucial role in various industrial sectors. Tuning PID parameters using optimization algorithms has garnered increasing interest due to its demonstrated efficiency. Several studies have validated the stability of ACO, PSO, and FPA algorithms, justifying their selection. In this article, simulation results showed that ACO, with a response time of 0.322s and an overshoot of 0.68%, was more effective than PSO, which had a response time of 0.768s and an overshoot of 13%. FPA had a response time of 0.347s, close to ACO, but a higher overshoot of 6%. In practice, several factors come into play, such as speed ripples caused by the speed sensor, and machine saturation, which must be considered to ensure practical implementation. After adjusting the PID parameters and integrating a low-pass filter in the feedback loop, ACO, with a response time of 0.596s and an overshoot of 1.68%, was very close to FPA, which had a response time of 0.644s and an overshoot of 0.81%. This comparison highlighted the advantages of the FPA algorithm, which is simple to use, requires fewer parameters to adjust, and takes less time than ACO. This study suggests the potential for implementing a hybrid FPA-ACO algorithm, leveraging the strengths of both algorithms.
Adaptive Frequency Control of an Isolated Microgrids Implementing Different Recent Optimization Techniques Hamid, Mohamed Nasr Abdel; Banakhr, Fahd A.; Mohamed, Tarek Hassan; Ali, Shimaa Mohamed; Mahmoud, Mohamed Metwally; Mosaad, Mohamed I.; Albla, Alauddin Adel Hamoodi; Hussein, Mahmoud M.
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1432

Abstract

In recent years, significant improvements have been made in the load frequency control (LFC) of interconnected microgrid (MG) systems, driven by the growing demand for enhanced power supply quality. However, challenges such as low inertia, parameter uncertainties, and dynamic complexity persist, posing significant hurdles for controller design in MGs. Addressing these challenges is crucial as any mismatch between demand load and power generation inevitably leads to frequency deviation and tie-line power interchange within the MG. This work introduces sophisticated optimization techniques (grey wolf optimization (GWO), whale optimization algorithm (WOA), and balloon effect (BE)) for LFC, focusing on the optimal online tuning of integral controller gain (Ki) for controlled loads. The WOA regulates the frequency of the system so variable loads can be accommodated and 6 MW of PV is added to the MG. A PV and a diesel generator-powered isolated single area MGs with electrical random loads are managed by the adaptive controller by regulating the frequency and power of the PV. Online tuning of integral controllers is possible using the WOA. A comparison is carried out between the WOA+BE and three other optimizers, namely the GWO, GWO+BE method, and the WOA. This paper shows the effect of add BE identifier to standard WOA and GWO. MATLAB simulation results prove that the BE identifier offers a significant advantage to the investigated optimizers in the issue of adaptive frequency stability even when disturbances and uncertainties are concurrent.
Control of a Multimode Double-Pendulum Overhead Crane System Using Input Shaping Controllers Hussien, Sharifah Yuslinda Syed; Jaafar, Hazriq Izzuan; Ghazali, Rozaimi; Ramli, Liyana; Johari, Mohd Khairul Azizat
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1520

Abstract

This paper investigates the impact of higher derivative input shaping for minimizing both oscillations, namely hook and payload of a multimode double-pendulum overhead crane (MDPOC) system. The MDPOC has greater nonlinearities and stronger internal couplings, especially when involving two oscillation frequencies with multimode dynamic effects. With a suitable system’s natural frequency and damping ratio of the hook and payload oscillations, multimode zero-vibration (ZV-ZV), multimode zero-vibration derivative (ZVD-ZVD) and multimode zero-vibration derivative-derivative (ZVDD-ZVDD) shapers are successfully designed. More interestingly, two scenarios under a fixed cable length and a payload hoisting are considered which are closer to the real practical crane.  Thus, an average travel length (ATL)-based shaper method is also considered to further verify the effectiveness and robustness of efficient hook and payload oscillation control under payload hoisting. All the multimode input shaping is simulated using the Matlab software. The simulation results of multimode ZVDD-ZVDD shaper successfully reduced in the overall hook and payload oscillations by 97.9% and 97.2%, respectively, compared to the unshaped system, whereas the multimode ATL-ZVDD shaper reduced hook and payload oscillations by 94.8% and 94.0%, respectively. In fact, the multimode ZVDD-ZVDD and multimode ATL-ZVDD shapers demonstrate the superiority in minimizing the hook and payload oscillations compared to the multimode ZV-ZV, multimode ZVD-ZVD, ATL-ZV and ATL-ZVD shapers. This significant reduction in oscillations enhances the precision and safety of real-world crane operations in industrial settings. It has been proven that considering the additional derivative of input shaping results in a higher level of hook and payload oscillations reduction.

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