Journal of Robotics and Control (JRC)
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.
Articles
708 Documents
<![CDATA[Monitoring DC Motor Based On LoRa and IOT ]]>
<![CDATA[Suhermanto, Dimas Ahmad Nur Kholis]]>;
<![CDATA[Aribowo, Widi]]>;
<![CDATA[Shehadeh, Hisham A.]]>;
<![CDATA[Rahmadian, Reza]]>;
<![CDATA[Widyartono, Mahendra]]>;
<![CDATA[Wardani, Ayusta Lukita]]>;
<![CDATA[Hermawan, Aditya Chandra]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i1.19642
<![CDATA[Electrical energy efficiency is a dynamic in itself that continues to be driven by electrical energy providers. In this work, long-range (LoRa) technology is used to monitor DC motors. In the modern world, IoT is becoming increasingly prevalent. Embedded systems are now widely used in daily life. More can be done remotely in terms of control and monitoring. LoRa is a new technology discovered and developing rapidly. LoRa technology addresses the need for battery-operated embedded devices. LoRa technology is a long-range, low-power technology. In this investigation, a LoRa transmitter and a LoRa receiver were employed. This study employed a range of cases to test the LoRa device. In the first instance, there are no barriers, whereas there are in the second instance. The results of the two trials showed that the LoRa transmitter and receiver had successful communication. In this study, the room temperature is used to control DC motors. So that the DC motor's speed adjusts to fluctuations in the room's temperature. Additionally, measuring tools and the sensors utilised in this investigation were contrasted. The encoder sensor and the INA 219 sensor were the two measured sensors employed in this study. According to the findings of the experiment, the tool was functioning properly.]]>
<![CDATA[LW-PWECC: Cryptographic Framework of Attack Detection and Secure Data Transmission in IoT ]]>
<![CDATA[Ranjith, J]]>;
<![CDATA[Mahantesh, K]]>;
<![CDATA[Abhilash, C N]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i1.20514
<![CDATA[In the present era, the number of Internet of Health Things (IoHT) devices and applications has drastically expanded. Security and attack are major issues in the IoHT domain because of the nature of its architecture and sorts of devices. Over the recent few years, network attacks have dramatically increased. Many detection and encryption techniques are existing however they lack accuracy, training stability, insecurity, delay etc. By the above concerns, this manuscript introduces a novel deep learning technique called Agnostic Spiking Binarized neural network with Improved Billiards optimization for accurate detection of network attacks and Light Weight integrated Puzzle War Elliptic Curve Cryptographic framework for secure data transmission with high security and minimal delay. Optimal features from the datasets are selected by volcano eruption optimization algorithm with better convergence for reducing the overall processing time. Wilcoxon Rank Sum and Mc Neymar’s tests are performed for proving the statistical analyses. The outcomes show that the introduced approach performs with an overall accuracy of 99.93% which is better than the previous techniques demonstrating the effectiveness.]]>
<![CDATA[Improving the Efficiency of Open Cathode PEM Fuel Cell Through Hydrogen Flow Control Using Wavelet-Clipping ]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 2 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i2.21227
<![CDATA[Open cathode proton exchange membrane fuel cells (OC-PEMFC) are devices that produce electrical energy through an electrochemical reaction between hydrogen and oxygen gas. Rapid load changes often lead to fluctuations in the flow of hydrogen entering the OC-PEMFC system. Increased load directly correlates with higher hydrogen gas consumption. However, if there is a delay in adjusting the gas flow rate to changes in load, it can trigger fluctuations in the amplitude and frequency of the output voltage. This fluctuation ultimately disrupts the stability of the power supply to the load, and reducing efficiency. Therefore, this paper presents a novel hybrid system that integrates wavelet and clipping techniques to regulate a more stable hydrogen flow, enhancing efficiency and accuracy under constant load conditions. A wavelet control system is used to mitigate noise, coupled with amplitude limitation through clipping techniques. This control system is implemented in OC-PEMFC model that is validated with experimental data. The performance analysis of this hybrid system reveals a 1.95 % increase in efficiency and attains high accuracy, as evidenced by a low ISE value of 0.028 during interference.]]>
<![CDATA[Model Predictive Control in Hardware in the Loop Simulation for the OnBoard Attitude Determination Control System ]]>
<![CDATA[Irwanto, Herma Yudhi]]>;
<![CDATA[Yusgiantoro, Purnomo]]>;
<![CDATA[Sahabuddin, Zainal Abidin]]>;
<![CDATA[Bura, Romie O.]]>;
<![CDATA[Artono, Endro]]>;
<![CDATA[Hakim, Arif Nur]]>;
<![CDATA[Nuryadi, Ratno]]>;
<![CDATA[Andiarti, Rika]]>;
<![CDATA[Mariani, Lilis]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 2 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i2.21613
<![CDATA[Rocket flight tests invariably serve a purpose, one of which involves area monitoring or aerial photography. Consequently, the rocket necessitates the installation of a camera that remains consistently oriented toward the Earth's surface throughout its trajectory. Thus, ensuring the rocket's stability and preventing any rotation becomes imperative. To achieve this, the Onboard Attitude Determination Control System (OADCS) was researched and developed, fully controlled by NI myRIO with Labview as the programming language, ensures the rocket's attitude control and maintains a rolling angle of 0 degrees during flight. The MyRIO oversees the retrieval of attitude and position data from the X-Plane flight simulator, offering feedback through actuator control. The development of the OADCS proceeded incrementally through stages utilizing the Software in the Loop Simulation (SILS) and Hardware in the Loop Simulation (HILS) techniques, to ensure the verification of the system's functionality before its application to the rocket for real flight testing. In the OADCS control scheme, Model Predictive Control (MPC) is chosen, and it is compared with a PID controller to serve as a benchmark for processing speed. Because the rocket's flight time is short and its speeds of up to Mach 4. The simulation results indicate that MPC can halt the rocket's rotation 12 times more rapidly than PID control. Additionally, the MPC's ability to maintain a zero-degree rotation can persist throughout the rocket's flight time. Employing SILS and HILS enhances the OADCS rocket development process by incorporating MPC, which holds promise for application in real rockets.]]>
<![CDATA[Robust Adaptive Iterative Learning Control for De-Icing Robot Manipulator ]]>
<![CDATA[Ngo, Thanh Quyen]]>;
<![CDATA[Tran, Thanh Hai]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 3 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i3.21791
<![CDATA[This paper introduces a new method of controlling uncertain robot using robust adaptive iterative learning control (RAILC) to track the trajectory in iterative operation mode. This method uses a PD controller combined with gain switching and forward learning techniques to predict the desired torque of the actuator. Using the Lyapunov method, this paper presents an RAILC control scheme for an uncertain robot system with structural and unstructured properties while ensuring the stability of the closed-loop system in the domain repeat. This study believes that this new control method can advance the field of robot control, especially in dealing with structured and unstructured uncertainties. It can help improve the flexibility and performance of robotic systems in real-world applications, such as automated manufacturing, transportation services, or healthcare. At the same time, providing simulation and test results demonstrates the effectiveness of the new control method in deicing high voltage power lines for robots.]]>
<![CDATA[Evaluating Security Mechanisms for Wireless Sensor Networks in IoT and IIoT ]]>
<![CDATA[Zhukabayeva, Tamara]]>;
<![CDATA[Buja, Atdhe]]>;
<![CDATA[Pacolli, Melinda]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 4 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i4.21683
<![CDATA[In the era of interconnected digital ecosystems, the security of Wireless Sensor Networks (WSN) emerges as a pivotal concern, especially within the domains of the Internet of Things (IoT) and the Industrial Internet of Things (IIoT). However, the very nature of WSNs—being distributed, resource-constrained, and often deployed in unattended environments—poses unique cybersecurity challenges. A main issue and challenge remains their Cybersecurity in communication. In this paper, we provide a systematic review focused on three themes including 1) techniques for secure communication in WSN; 2) algorithms and methods for intrusion detection in WSN; and 3) IoT and IIoT security concerning WSN. It has provided the results of its own for the publications made in the data analysis of three themes. The paper also has a simulation experiment to investigate the behavior of WSNs under sinkhole attacks—one of the prevalent threats to network integrity. Utilizing the Contiki OS Cooja simulator, the experiment carefully evaluates the performance of existing detection algorithms and introduces a novel method for identifying and neutralizing malicious nodes. Our simulation discloses unconventional communication patterns during sinkhole attacks running RPL protocol, emphasizing the effectiveness of our detection mechanisms against cyber threats. Particularly, the introduction of a malicious node (Node 13) significantly disrupted network communication, with traditional security mechanisms failing to immediately detect and isolate the threat. The scope of future research work will include the broader spectrum of cyber threats beyond sinkhole attacks, exploring advanced detection mechanisms, and machine learning-based security protocols for enhanced trust and transparency in WSN communications.]]>
<![CDATA[Design Intelligent Control Based on Fuzzy Neural Network and GA Algorithm for Prediction and Identification ]]>
<![CDATA[Nguyen, Van-Truong]]>;
<![CDATA[Pham, Duc-Hung]]>;
<![CDATA[Nguyen, Hoang-Nam]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 4 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i4.22115
<![CDATA[One of the central aspects in system identification and prediction is dealing with nonlinearity and uncertainties. This need involves the design of a novel method for achieving high efficiency and effectiveness, which is crucial for several applications. In this paper, a new intelligent control based on a hybrid fuzzy neural network (FNN) combined with a genetic algorithm (GA) is proposed for the prediction and identification of nonlinear systems. Two adaptations are considered in the proposed method: the backpropagation (BP) algorithm and the genetic algorithm method to correct various parameters in the neural network. Through adjustment, the proposed method not only achieves error convergence efficiently and quickly but also ensures continuous error reduction while avoiding the limitation of the regional optimal solution. Mackey-Glass differential delay and fuzzy neural system are utilized for system prediction and identification, respectively. Finally, the performance of the proposed method is justified through an application on a nonlinear system. Based on the findings, this paper proposed a hybrid strategy combining BP-GA and FNN where the outcome is greatly influenced by the balance of accuracy and computational efficiency.]]>
<![CDATA[Enhanced Transformer Protection Using Fuzzy-Logic-Integrated Differential Relays: A Comparative Study with Rule-based Methods ]]>
<![CDATA[Hussein, Raad Ibrahim Hussein]]>;
<![CDATA[Gökşenli, Nurettin]]>;
<![CDATA[Bektaş, Enes]]>;
<![CDATA[Teke, Mustafa]]>;
<![CDATA[Tümay, Mehmet]]>;
<![CDATA[Yaseen, Ethar Sulaiman Yaseen]]>;
<![CDATA[Bektaş, Yasin]]>;
<![CDATA[Taha, Taha A.]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 5 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i5.21937
<![CDATA[The power transformers are the important part of electrical networks where transformer reliability and operational lifetime depends on sufficiently accurate and reliable protective means. Other traditional forms of differential protection that were developed initially also suffer from the inability to distinguish between a fault and normal operation such as inrush currents in transformers and CT saturation. This paper presents the development of an improved differential relay augmented by Fuzzy-Logic Control System (FLC), to improve (a) dependability, (b) performance of the existing transformer protection systems, and (c) accuracy in fault identification possible due to uncertainty and non-linearity in transformer operation. They include the proposed methodology compared to the traditional Rule-based current differential method in outlining the protection settings. MATLAB/Simulink model of the power transformer and protection methods suggested in the study form a part of the investigation. Computer simulations show that the presented scheme provides a substantial increase in the speed and resolution of fault detection and fault types identification relating to current differential method based on the Rule. The system’s accuracy rate is the average of 98% for internal faults and 95% for external faults while its response time is 25ms for internal faults and 30ms for external faults. Furthermore, the Fuzzy-Logic-based system has an 90% efficiency in detect the defect and 85% efficiency in identify the inrush currents. The findings of this research prove that the differential relay based on Fuzzy-Logic enhances the flexibility and reliability of transformer protection and opens the road to the introduction of further improvements in the intelligent protection systems in the future.]]>
<![CDATA[Integrated Room Monitoring and Air Conditioning Efficiency Optimization Using ESP-12E Based Sensors and PID Control Automation: A Comprehensive Approach ]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 6 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v4i6.18868
<![CDATA[This study addresses the critical need for efficient room monitoring and air conditioning systems, particularly in educational settings like the STMIK STIKOM Indonesia campus. The paper introduces a novel approach that combines ESP-12E based sensors with Proportional-Integral-Derivative (PID) control automation to optimize air conditioning efficiency. Utilizing an ESP-12E microcontroller, the study designed and implemented a room monitoring tool equipped with DHT22 and BH1750 sensors for accurate measurement of temperature, humidity, and light intensity. We also explores the integration of a PID control system into an existing air conditioning (AC) unit. The PID controller was fine-tuned to maintain a stable indoor temperature of 25oCelsius, even when subjected to external heat loads, such as ten LED lamps. The effectiveness of this system was quantified through real-time monitoring of temperature, humidity, and energy consumption, both pre- and post-implementation. Results indicated a rapid and stable response from the PID controller, achieving an amplitude of 1 within 0.08 seconds, thereby confirming its successful tuning and adaptability. We found that this study has broader implications for enhancing energy efficiency and creating conducive learning environments. However, it is worth noting that the research was conducted under specific conditions, and further studies could explore its applicability in different settings.]]>
<![CDATA[Abnormality Determination of Spermatozoa Motility Using Gaussian Mixture Model and Matching-based Algorithm ]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 5, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.v5i1.20686
<![CDATA[Sperm analysis is an initial step in the examination conducted to identify infertility cases in humans. One aspect of sperm analysis involves observing the movement of spermatozoa and determining whether it is normal or abnormal. Normal spermatozoa movement is characterized by progressive motion at an average speed of 20 µm/second, while abnormal movement includes slow or non-motile spermatozoa. Traditional methods can be employed to assess the normality or abnormality of sperm movement, but they have drawbacks such as time-consuming procedures and diverse results depending on the expertise of the examiner. On the other hand, utilizing Computer-Assisted Sperm Analysis (CASA) equipment provides consistent results, albeit at a relatively high cost. Therefore, this research proposes an alternative method for determining sperm movement abnormalities using the Gaussian Mixture Model (GMM) for background subtraction and a matching-based algorithm to track and analyze the formed trajectories, distinguishing between normal and abnormal sperm movement. Human spermatozoa in real-time are used, and their movements are recorded in video format using a bright field microscope. The testing results for determining sperm movement abnormalities based on the GMM method and matching-based algorithm were successful, particularly in videos recorded at 50 fps recording speed, 20 minutes of liquefaction time, and 40x microscope lens magnification. This condition exhibited the highest average accuracy, with a tracking accuracy of 77.3% and an average accuracy for determining sperm motility abnormalities of 87.7%. Therefore, the combined tracking of sperm movement based on the GMM method and matching-based algorithm can be utilized to identify abnormalities in the movement of human spermatozoa.]]>
