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Journal of Robotics and Control (JRC)
Published by Universitas Muhammadiyah Yogyakarta
ISSN : 27155056     EISSN : 27155072     DOI : https://doi.org/10.18196/jrc
Core Subject : Science, Engineering,
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering
Journal of Robotics and Control (JRC) is an international open-access journal published by Universitas Muhammadiyah Yogyakarta. The journal invites students, researchers, and engineers to contribute to the development of theoretical and practice-oriented theories of Robotics and Control. Its scope includes (but not limited) to the following: Manipulator Robot, Mobile Robot, Flying Robot, Autonomous Robot, Automation Control, Programmable Logic Controller (PLC), SCADA, DCS, Wonderware, Industrial Robot, Robot Controller, Classical Control, Modern Control, Feedback Control, PID Controller, Fuzzy Logic Controller, State Feedback Controller, Neural Network Control, Linear Control, Optimal Control, Nonlinear Control, Robust Control, Adaptive Control, Geometry Control, Visual Control, Tracking Control, Artificial Intelligence, Power Electronic Control System, Grid Control, DC-DC Converter Control, Embedded Intelligence, Network Control System, Automatic Control and etc.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 708 Documents
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Fuzzy Logic Control and PID Controller for Brushless Permanent Magnetic Direct Current Motor: A Comparative Study Shuraiji, Ahlam Luaibi; Shneen, Salam Waley
Journal of Robotics and Control (JRC) Vol 3, No 6 (2022): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i6.15974

Abstract

Electrical machines based on permanent magnet material excitations have been applied in many sectors since they are distinguished by their high torque-to-size ratio and offer high efficiency. Brushless permanent magnetic direct current (BLPMDC) motors are one type of these machines. They are preferable over conventional DC motors. one of the main challengings of the BLPMDC motor drives is the inherited feature of nonlinearity. Therefore, a conventional PID controller would not be an efficient choice for the speed control of such motors. The object of this paper is to design an efficient speed control for the BLPMDC motor. The proposed controller is based on the Fuzzy logic technique. MATLAB/ Simulink has been employed to design and test the drive system. Simulations were carried out for three cases, the first without a controller, the other using conventional control, and the third using expert systems. The results proved the possibility of improving the engine's working performance using the control systems. They also proved that the adoption of expert systems is better than the traditional nonlinear systems. The simulation response shows that the Rise Time(tr) at PID equals 66.306ms, while it equals 19.530ms for the Fuzzy logic controller. Moreover, Overshoot for PID and Fuzzy logic controller are 6.989% and 1.531%, respectively. On the other hand, undershoot is equal to 1.788% and 11.924% for PID and Fuzzy logic controller, respectively.
Methodology for the Development of Radar Control Systems for Flying Targets with an Artificially Reduced RCS Igor Parkhomey; Juliy Boiko; Oleksander Eromenko
Journal of Robotics and Control (JRC) Vol 3, No 4 (2022): July
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i4.15440

Abstract

The article explores methods for detecting and tracking air targets in radar with an artificially reduced radar cross-section (RCS). A technique for control the radar antenna system using an adaptive method is presented, which is based on adapting the system to the conditions of information uncertainty due to fluctuations in the excitation signal of the radar target's radar-absorbing coating. Known methods of radar aircraft (active and passive, which do not take into account the structure of the coating of the aircraft) do not allow obtaining information about an air target with an artificially reduced RCS. The main contribution of this article is the development of radar and control methods based on the resonant frequency-phase interaction of the microwave electromagnetic field with the crystal structure of the radar absorbing coating of the aircraft. The stages of antenna system control based on the "frequency-phase detection method", "passive-active" tracking method, and "adaptive method" of antenna control have been studied. To test the proposed methods, an experiment was conducted to determine the transient process in the control system under conditions of information uncertainty. As a result of the experiment, the probability of tracking the target is increased by 14-19%. The findings will be useful for developers of radar and control systems for modern air facilities with an artificially reduced RCS.
Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022) Sekhar, Ravi; Shah, Pritesh; Iswanto, Iswanto
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.15453

Abstract

Robotics forms an integral part of industry 4.0, the industrial revolution of the 21st century. This paper presents a bibliometric analysis of Web of Science (WoS) indexed publications addressing this emerging field from 2011 till June 2022. WoS research publications were firstly analysed along multiple verticals such as annual counts, types, publishing sources, research directions, researchers, organizations, and countries. Next, co-authorship collaborations among authors, organizations, and countries were discovered. This was followed by an analysis of co-occurring keywords related to robotics in industry 4.0. Finally, a detailed citation analysis was carried out to unearth citation linkages among authors, institutions, documents, nations, and journals. Latest trends, under-investigated topics, and future directions are also discussed. Primary results indicate that more than 3000 articles are being published annually in this emerging field, with a total of 18,893 documents published in WoS during the last decade. The 'IEEE Access', Chinese Academy of Science, Wang Y. (USA), and the USA emerged as the topmost productive journal, institution, author, and nation. Porpiglia Francesco (Italy), Chinese Academy Science and USA obtained the highest co-authorship total link strength (TLS); whereas Lee Chengkuo (Singapore), China, Chinese Academy Science, and the IEEE Access scored the highest citation TLS among authors, countries, organizations, and sources respectively. Machine learning (ML) emerged as the highest co-occurring keyword, followed by artificial intelligence (AI). Computer Science emerged as the most trending research domain, followed by general applications. In the future, ML and AI will advance more sophisticated robots in industry 4.0 systems.
Interaction Motion Control on Tri-finger Pneumatic Grasper using Variable Convergence Rate Prescribed Performance Impedance Control with Pressure-based Force Estimator Irawan, Addie; Azahar, Mohd Iskandar Putra; Pebrianti, Dwi
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.16316

Abstract

Pneumatic robot is a fluid dynamic based robot system which possesses immense uncertainties and nonlinearities over its electrical driven counterpart. Requirement for dynamic motion handling further challenged the implemented control system on both aspects of interaction and compliance control. This study especially set to counter the unstable and inadaptable proportional motions of pneumatic robot grasper towards its environment through the employment of Variable Convergence Rate Prescribed Performance Impedance Control (VPPIC) with pressure-based force estimation (PFE). Impedance control was derived for a single finger of Tri-finger Pneumatic Grasper (TPG) robot, with improvement being subsequently made to the controller’s output by appropriation of formulated finite-time prescribed performance control. Produced responses from exerted pressure of the maneuvered pneumatic piston were then recorded via derived PEE with adherence to both dynamics and geometry of the designated finger. Validation of the proposed method was proceeded on both circumstances of human hand as a blockage and ping-pong ball as methodical representation of a fragile object. Developed findings confirmed relatively uniform force sensing ability for both proposed PEE and load sensor as equipped to the robot’s fingertip with respect to the experimented thrusting and holding of a human hand. Sensing capacity of the estimator has also advanced beyond the fingertip to enclose its finger in entirety. Whereas stable interaction control at negligible oscillation has been exhibited from VPPIC against the standard impedance control towards gentle and compression-free handling of fragile objects. Overall positional tracking of the finger, thus, justified VPPIC as a robust mechanism for smooth operation amid and succeed direct object interaction, notwithstanding its transcendence beyond boundaries of the prescribed performance constraint.     
Current Trends in Intelligent Control Neural Networks for Thermal Processing (Foods): Systematic Literature Review Dewi Marfuah; Nurul Kholisatul 'Ulya; Dewi Pertiwi Dyah Kusudaryati; Agung Setya Wardana; Eko Nugroho
Journal of Robotics and Control (JRC) Vol 3, No 4 (2022): July
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i4.15232

Abstract

Thermal processing is a technique for sterilizing foods through heating at high temperatures. Thermal processing plays a significant role in preserving foods economically, efficiently, reliably, and safely. Control in thermal processing of foods is necessary to avoid any decrease in food quality, i.e., color change, reduced content, sensory quality, and nutrition. Artificial Neural Network (ANN) has been developed as a computing method in research and developments on thermal processing methods to discover one suitable for food processing without damaging food quality. To this date, ANN has been used in food industries for modeling many processes. The paper aims to identify the latest trend in intelligent neural network control for the thermal processing of foods. The paper conducted a systematic literature review with five research questions using Preferred Reporting Items for Systematic Review (PRISMA). According to screening results and article selection, 240 potential articles have fulfilled the inclusion criteria. Then, each article was explored to identify the advantage and the advance of intelligent network control in thermal food processing. It can be concluded that the technology in information and computations of food processing has rapidly developed and advanced through the utilization of a combination of ANN with fuzzy logic and/or genetic algorithms.
Robust Flux and Speed State Observer Design for Sensorless Control of a Double Star Induction Motor Mahmoud A. Mossa; Houari Khouidmi; Alfian Ma’arif
Journal of Robotics and Control (JRC) Vol 3, No 4 (2022): July
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i4.15667

Abstract

In this paper, a robust flux and speed observer for sensorless control of a double star induction motor is presented. Proper operation of vector control of the double star induction motor requires reliable information from the process to be controlled. This information can come from mechanical sensors (rotational speed, angular position). Furthermore, mechanical flux and speed sensors are generally expensive and fragile and affect the reliability of the system. However, the control without sensors must-have performance that does not deviate too much from that which we would have had with a mechanical sensor. In this framework, this work mainly deals with the estimation of the flux and speed using a robust state observer in view of sensorless vector control of the double star induction motor. The evaluation criteria are the static and dynamic performances of the system as well as the errors between the reference values and those estimated. Extensive simulation results and robustness tests are presented to evaluate the performance of the proposed sensorless control scheme. Furthermore, under the same test conditions, a detailed comparison between the proposed state observer and the sliding mode-MRAS technique is carried out where the results of its evaluation are investigated in terms of their speed and flux tracking capability during load and speed transients and also with parameter variation. It is worth mentioning that the proposed state observer can obtain both high current quality and low torque ripples, which show better performance than that in the MRAS system.
A Comprehensive Overview of Classical and Modern Route Planning Algorithms for Self-Driving Mobile Robots N. S. Abu; W. M. Bukhari; M.H. Adli; S. N. Omar; S. A. Sohaimeh
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.14683

Abstract

Mobile robots are increasingly being applied in a variety of sectors, including agricultural, firefighting, and search and rescue operations. Robotics and autonomous technology research and development have played a major role in making this possible. Before a robot can reliably and effectively navigate a space without human aid, there are still several challenges to be addressed. When planning a path to its destination, the robot should be able to gather information from its surroundings and take the appropriate actions to avoid colliding with obstacles along the way. The following review analyses and compares 200 articles from two databases, Scopus and IEEE Xplore, and selects 60 articles as references from those articles. This evaluation focuses mostly on the accuracy of the different path-planning algorithms. Common collision-free path planning methodologies are examined in this paper, including classical or traditional and modern intelligence techniques, as well as both global and local approaches, in static and dynamic environments. Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. In this study, we outline the ideas, benefits, and downsides of modeling and path-searching technologies for a mobile robot.
Design and Fabrication of a Low-Cost System for Smart Home Applications Ammar Ali Sahrab; Hamzah M. Marhoon
Journal of Robotics and Control (JRC) Vol 3, No 4 (2022): July
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i4.15413

Abstract

Smart systems and security got impressive attention and development in recent years, which have been appeared in the terms of smart homes, intelligent security, and the Internet of Things (IoT). Home automation comprises the controlling of the electrical appliances in the home wirelessly or automatically. Many different integrated circuits, sensors, modules, and embedded systems are available to be compatible to integrate with smart homes. In order to apply the concept of smart homes, many issues should be considered like as providing a user-friendly, reliable, secure, and cost-effective. In this paper, an effective and low-cost smart home system is designed and implemented based on the Arduino microcontroller boards with its compatible modules. The proposed work employed many types of sensors to carry out the tasks for the smart home for a couple of the essential segments, the first one is home security and the latter one is home automation. The antitheft home segment is based on the laser source directed on the light-dependent resistor and infrared sensor; once the thief tries to cut the laser or passes beside the sensor, the alarm will be switched on. The later segment aims to detect the fire occurring by the means of the flame sensor, gas leakage detection by the MQ-05 sensor, servo motor to opening/closing the garage door, LCD to display the status of the all-utilised sensors, and finally, the Bluetooth module to controlling the garage door wirelessly. To increase the system performance and reliability the Arduino Nano and the Arduino Leonardo board are utilised. 
Design and Implementation of a Reliable and Secure Controller for Smart Home Applications Based on PLC Khairullah, Shawkat Sabah; Sharkawy, Abdel-Nasser
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.15972

Abstract

Programmable logic controllers (PLCs) are increasingly being used to realize modern safety-critical instrumentation and control (IC) applications. Examples of these applications are industrial automation and control systems, plant process safety protection systems, smart home systems and digital IC systems embedded in nuclear power plants (NPPs) that require high levels of performance, reliability, and flexibility. The PLC is a flexible, programmable, and robust digital device that can execute all logical and mathematical runtime functions of the IC application and operate in harsh-critical environments. This paper proposes a PLC-based home security controller based on the ladder logic programming model. The design, analysis, and hardware implementation of this controller are presented in this paper. The designed system consists of three basic modules which are a sensing module used for reading the data of the input field devices for the smart home application, a computation-based decisional module used for executing the programming model, and an actuating module used for sending the control commands to the output field devices. The proposed home security system utilized different types of sensors such as a laser photoelectric sensor, a motion or proximity sensor, and a limit switch. In addition, a siren speaker, a light tower including three lights red, yellow, and green, two push-pull switches and emergency push-pull buttons were used as control inputs and output indicators in the implementation of this work This designed system is implemented on the Allen-Bradley CompactLogix PLC controller and Human Machine Interface (HMI) panel programmed as the graphical user interface. The experimental simulation results of the real hardware connection demonstrate that the proposed system is reliable, safe, and feasible for smart home security applications.
A Comparative Study Between Convolution and Optimal Backstepping Controller for Single Arm Pneumatic Artificial Muscles Ahmed, Amna Suri; Kadhim, Saleem Khalefa
Journal of Robotics and Control (JRC) Vol 3, No 6 (2022): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i6.16064

Abstract

This study was based on the dynamic modeling and parameter characterization of the one-link robot arm driven by pneumatic artificial muscles. This work discusses an up-to-date control design based on the notion of a conventional and optimal backstepping controller for regulating a one-link robot arm with conflicting biceps and triceps positions supplied by pneumatic artificial muscles. The main problems found in systems that utilize pneumatic artificial muscle as actuators are primarily the large uncertainties, non-linearities, and time-varying features that severely impede movement performance in tracking control. In consideration of the uncertainty, high nonlinearity, and external disturbances that can exist during the motion. Lyapunov-based backstepping control technique was utilized to assure the stability of the system with improved dynamic performance. The bat algorithm optimization method is utilized in order to modify the variables used in the design of the controller to enhance the efficiency of the suggested controller. According to the conclusions, a quantitative comparison of the response in the PAM actuated the arm model in the current study and earlier investigations with the Backstepping controlled system revealed fair agreement with a variation of 37.5% from the optimal classical synergetic controller. In addition, computer simulations were utilized in order to compare the effectiveness of the proposed conventional controls and the optimal background. It has been proven that an optimal controller can control the uncertainties and maintain the controlled system’s stability.

Page 30 of 71 | Total Record : 708

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