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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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Short-Term Solar PV Power Generation Day-Ahead Forecasting Using Artificial Neural Network: Assessment and Validation Abdel-Nasser Sharkawy; Mustafa M. Ali; Hossam H. H. Mousa; Ahmed S. Ali; G. T. Abdel-Jaber
International Journal of Robotics and Control Systems Vol 2, No 3 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i3.780

Abstract

Solar photovoltaics (PV) is considered an auspicious key to dealing with energy catastrophes and ecological contamination. This type of renewable energy is based on climatic conditions to produce electrical power. In this article, a multilayer feedforward neural network (MLFFNN) is implemented to predict and forecast the output power for a solar PV power station. The MLFFNN is designed using the module temperature and the solar radiation as the two main only inputs, whereas the expected power is its output. Data of approximately one week (6-days) are obtained from a real PV power station in Egypt. The data of the first five days are used to train the MLFFNN. The training of the designed MLFFNN is executed using two types of learning algorithms: Levenberg-Marquardt (LM) and error backpropagation (EBP). The data of the sixth day, which are not used for the training, are used to check the efficiency and the generalization capability of the trained MLFFNN by both algorithms. The results provide evidence that the trained MLFFNN is running very well and efficiently to predict the power correctly. The results obtained from the trained MLFFNN by LM (MLFFNN-LM) are compared with the corresponding ones obtained by the MLFFNN trained by EBP (MLFFNN-EBP). From this comparison, the MLFFNN-LM has slightly lower performance in the training stage and slightly better performance in the stage of effectiveness investigation compared with the MLFFNN-EBP. Finally, a comparison with other previously published approaches is presented. Indeed, predicting the power correctly using the artificial NN is useful to avoid the fall of the power that maybe happen at any time.
An Examination of the Secure Chaos of 5G Wireless Communication Based on the Intelligent Internet of Things Janan Farag Yonan
International Journal of Robotics and Control Systems Vol 2, No 4 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i4.769

Abstract

The implementation of an intelligent system for network control and monitoring that is built on an Internet of Things (IoT) is a focus of this line of research, with the end objective of improving the level of precision inside the network and its applications. You did indeed read it correctly; the system that is being referred to here is a deep neural network. The manner that it is constructed makes it possible for the layer that cannot be seen to contain more data. The application of element-modified deep learning and network buffer capacity control helps to improve the overall service quality that is provided by each sensor node. One method that can be applied to the process of instructing a machine to pay more attention includes deep learning in its various incarnations. The team was able to do calculations with a precision of 96.68 percent and the quickest execution time, thanks to the usage of wireless sensors. Using a sensor-based technique that has a brief implementation period, this piece has a degree of accuracy of 97.69 % when it comes to detecting and classifying proxies, and it does so using a method that is very efficient. On the other hand, our research represents a significant leap forward in comparison to earlier studies due to the fact that we were able to accurately identify and categorize a wide variety of invasions and real-time proxies.
Adaptive Neuro-Fuzzy Self Tuned-PID Controller for Stabilization of Core Power in a Pressurized Water Reactor Hany Abdelfattah; Said A. Kotb; Mohamed Esmail; Mohamed I. Mosaad
International Journal of Robotics and Control Systems Vol 3, No 1 (2023)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v3i1.710

Abstract

There has been a lot of interest in generating electricity using nuclear energy recently. This interest is due to the features of such a source of energy. The main part of the nuclear energy system is the reactor core, especially the most widely used Pressurized Water Reactor (PWR). This reactor is the hottest part of the nuclear system; security risks and economic possibilities must be considered. Controlling this reactor can increase the security and efficiency of nuclear power systems. This study presents a dynamic model of the (PWR), including the reactor's core, the plenums of the upper and lower, and the connecting piping between the reactor core and steam generator. In addition, an adaptive neuro-fuzzy (ANFIS) self-tuning PID Controller for the nuclear core reactor is presented. This adaptive controller is used to enhance the performance characteristics of PWR by supporting the profile of the reactor power, the coolant fuel, and hot leg temperatures. The suggested proposed ANFIS self-tuning controller is estimated through a comparison with the conventional PID, neural network, and fuzzy self-tuning controllers. The results showed that the proposed controller is best over traditional PID, neural network, and fuzzy self-tuning controllers. All simulations are throughout by using MATLAB/SIMULINK.
Active Control System Applied to Vibration Level Control in High-Speed Elevators Marcos Gonçalves; Jose M. Balthazar; Clivaldo Oliveira; Maria E. K. Fuziki; Giane G. Lenzi; Angelo Marcelo Tusset
International Journal of Robotics and Control Systems Vol 2, No 3 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i3.768

Abstract

This work presents an active control system applied to vibration level reduction in high-performance vertical transport, aiming at improving the passengers’ comfort in high-speed elevators. The control system design includes the use of a Proportional Integral Derivative (PID) control. Three strategies were proposed in order to achieve a 90% reduction in the vibration amplitudes: (I) the consecutive reduction of 90% of the displacements, (II) the consecutive reduction of 90% of the velocity, and (III) the consecutive reduction of 90% of the acceleration. The presentation of these three proposals allows their application for the use of different sensors. The performance of each strategy was evaluated through mathematical modeling and numerical simulations of a vertical transport with 4 degrees of freedom, submitted to excitations arising from rail deformations. Vibration and comfort levels in the cabin were numerically analyzed, taking into account ISO 2631 and BS 6841 standards for elevator lateral acceleration level and comfort level felt by passengers. Numerical simulations showed that the force required to reduce the vibration levels is practically the same for the three proposed strategies. However, strategy (III) – the successive reduction of 90% of acceleration – proved to be more efficient at improving passengers’ comfort level when compared to the other two strategies.
Spectrum Sensing Utilizing Power Threshold and Artificial Intelligence in Cognitive Radio Zainab Ali Abbood; Noor Alhuda F. Abbas; Basma Makki
International Journal of Robotics and Control Systems Vol 2, No 4 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i4.771

Abstract

The purpose of this paper was to take a preventative approach to predict the transmission status of the primary user (PU) on the white spectrum throughout the duration of the simulation. We intend to reduce the computational simulation budget to eliminate user interference by precise spectrum sensing handoff. We develop PU behaviors to use a time waiting estimate methodology that gives band occupancy time intervals. The proposed strategy may also lessen risks associated with flexible clients and adapt to changing channels. Real-time applications will use ANN range sharing, which reduces transmission delay, while high-throughput applications will use PTHD range sharing. Since noise as well as obscuring effects after each transmission plan, their proximity in the channel can influence range detection. This finding is in line with published investigations. Most range detection systems compare frequency test results with the operating channel's control scope thickness. The paper met design objectives by developing a noise-independent sensing methodology with proactive time estimation. The trial is accomplished with reduced cost and latency.
Analysis and Challenges in Wireless Networked Control System: A Survey Mutaz M. Hamdan; MagdiSadek Mostafa Mahmoud
International Journal of Robotics and Control Systems Vol 2, No 3 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i3.731

Abstract

A wireless networked control system (WNCS) consists of a dynamic system to be controlled, sensors, actuators, and a remote controller. A WNCS has two types of wireless transmissions, i.e., the sensor's measurement transmission to the controller and the controller's command transmission to the actuator. In this paper, we are surveying the literature on the communication networks in WNCSs and the challenges related to them, such as the communication standards, delay, Packet dropout, and delay jitter. Then, the control approaches in the design of a WNCS are presented, including the interactive design approaches and the joint design approaches. Also, several applications of WNCSs have been discussed in terms of their structure, functionality, and control design. These applications include Intra-Vehicle Wireless networks, Wireless Avionics Intra-Communication, Building Automation, and Water pumping. After that, security issues in WNCSs from a control engineering point of view are detailed while focusing on the major kinds of cyber attacks affecting WNCSs. Finally, future directions and conclusions are summarized at the end of the paper.
Deep Learning-based Attack Detector for Bilateral Teleoperation Systems Yousif Ahmed Al-Wajih; Mutaz M. Hamdan; Turki Bin Mohaya; Magdi S. Mahmoud; Nezar M. Al-Yazidi
International Journal of Robotics and Control Systems Vol 3, No 1 (2023)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v3i1.822

Abstract

A teleoperation system is referred to as a plant that is controlled remotely, and it is often composed of a human operator, a local master manipulator, and a remote slave manipulator, all connected by a communication network. Bilateral teleoperation systems (BTOS) include transmissions in both the forward and backward directions between the master and slave. This paper discusses a class of (BTOS) focusing on the security of the system after modeling the master and slave robots mathematically. The false data injection attack is examined, where the attacker may inject false data into the states that are being exchanged between the master and slave robots. The vulnerability of BTOS, where the attack destabilizes the system, is presented. A deep learning-based detection technique is proposed to detect the presence of false data injection attacks. The deep learning model with convolution neural network structure is trained and tested with considering complex attacks where the attacker has full knowledge of the system and proficiency to emanate and control the target system. The proposed model achieves 96\% validation accuracy, and the efficacy of the proposed deep learning detector is demonstrated and tested into the BTOS.
Induction Motor Torque Measurement using Prony Brake System and Close-loop Speed Control Hari Maghfiroh; Arthur Joshua Titus; Augustinus Sujono; Feri Adriyanto; Joko Slamet Saputro
International Journal of Robotics and Control Systems Vol 2, No 3 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i3.782

Abstract

Three-phase induction motors are the main drivers of the industrial world because of their low price and good reliability. However, this type of motor does not have built-in speed control. These problems can be overcome by utilizing the Variable Frequency Drive (VFD) inverter. This research investigates the induction motor's characteristics in every load condition and combines a VFD inverter with an external speed controller based on Arduino. The motor is mounted on a Prony brake testbed frame to measure the motor's torque and mechanical power. The test results show the highest torque value obtained is 0.57 Nm, and the highest output power value is 0.042 kW. The motor cannot maintain the setpoint speed after loading in the open-loop control system. Meanwhile, the closed-loop control system has been successfully implemented, and the motor can return the speed to the setpoint value after loading, with an average settling time of 14.67 seconds.
Design of Hybrid Controller using Qualitative Simulation Internal Modeling for Inverted Pendulum Chunrong Xia; Irfan Qaisar; Muhammad Shamrooz Aslam
International Journal of Robotics and Control Systems Vol 2, No 4 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i4.777

Abstract

Multiple model methods for nonlinear dynamical system control are appealing because local models can be simple and obvious, and global dynamics can be studied in terms of transitions between small operating zones. In this study, we propose that using qualitative models strengthens the multiple model method even more by enabling each local model to explain a huge class of effective nonlinear dynamical systems. Furthermore, reasoning using qualitative models reveals weak necessary conditions sufficient to verify qualitative features like stability analysis. The authors show the method by creating a global controller for the free pendulum. In addition, local controllers are specified and validated by comparing their patterns to basic general qualitative models. Our proposed procedure establishes qualitative limitations on controller designs that are sufficient to ensure the necessary local attributes and to establish feasible transitions between local areas for the existing problems. As a result, the continuous phase picture may be reduced to a simple transitional graph. The degrees of freedom in the system that are not bound by the qualitative description are still accessible to the designer for optimization for any other purpose. An example of a pendulum plant illustrates the effectiveness of the proposed method.
Adaptive PID Fault-Tolerant Tracking Controller for Takagi-Sugeno Fuzzy Systems with Actuator Faults: Application to Single-Link Flexible Joint Robot Mohamed Elouni; Habib Hamdi; Bouali Rabaoui; Naceur BenHadj Braiek
International Journal of Robotics and Control Systems Vol 2, No 3 (2022)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v2i3.762

Abstract

This paper considers the problem of Fault Tolerant Tracking Control (FTTC) strategy design for nonlinear systems using Takagi-Sugeno (T-S) fuzzy models with measurable premise variables affected by actuator faults subject to unknown bounded disturbances (UBD). Firstly, the Adaptive Fuzzy Observer (AFO) is proposed to estimate the faults. Based on the information provided by this observer, an active fault tolerant tracking controller described by an adaptive Proportional-Integral-Derivative (PID) structure has been developed to compensate for the actuator fault effects and to guarantee the trajectory tracking of desired outputs to the reference model despite the presence of actuator faults. The stability and the trajectory tracking performances of the proposed approach are analyzed based on the Lyapunov theory. Sufficient conditions can be obtained and solved for the design of the controller, and the observer gains using Linear Matrix Inequalities (LMIs). Finally, the effectiveness of the proposed technique is illustrated by using a single-link flexible joint robot.

Page 9 of 37 | Total Record : 361

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