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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 21 Documents
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Search results for , issue "Vol 5, No 6 (2024)" : 21 Documents clear
A Model of Proactive-Reactive Job Shop Scheduling to Tackle Uncertain Events with Greedy Randomized Adaptive Search Procedure Nisar, Muhammad Usman; Ma'ruf, Anas; Cakravastia, Andi; Halim, Abdul Hakim
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22208

Abstract

Despite substantial research on job shop scheduling (JSS), there is a gap owing to the lack of a unified framework that considers exact, heuristic, and metaheuristic methods for JSS. This study addressed this gap by presenting a comprehensive approach. The study offered following contributions in this regard: analyzed the exact optimization method for benchmarking, investigated a greedy algorithm (G_r A) for faster solutions, and implemented a novel Greedy Randomized Adaptive Search Procedure (GRASP) to achieve high-quality solutions with computational effectiveness. Additionally, this study considered serious dynamic events (SDE) such as new job arrivals (NJA), rush order (RO), machine failures (MF), and scheduled machine maintenance (SMM), as scheduling disruptions and proposed a proactive-reactive rescheduling strategy, with right-shift (RF) and regeneration (Reg) methods using a hybrid (periodic and event-driven) policy to tackle them. Results showed that the exact methods are optimal but computationally intensive, G_r A are faster but suboptimal, and GRASP strike a balance, delivering high-quality solutions with only a 3.43% gap from exact methods while maintaining computational efficiency. Additionally, RF method effectively handled MF, while Reg efficiently integrated NJA, RO, and SMM. Overall, this study offered a comprehensive approach to JSS, enhancing applicability in manufacturing environments.
Overvoltage and Oscillation Analysis for a Full-Bridge Isolated DC-DC Converter Avdeev, Boris A.; Vyngra, Aleksei V.; Zhilenkov, Anton A.; Chernyi, Sergei G.; Degtyarev, Andrey; Kustov, Aleksandr; Zinchenko, Anton
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23120

Abstract

The paper deals with determining and eliminating overvoltage’s and ripples from the output of a high-frequency inverter bridge in a full-bridge DC converter. These oscillations can cause overvoltage on the elements of the power converter, which in turn can lead to false triggering of semiconductor keys or their failure. Schematic diagrams of the bridge are given; the principle of its operation is described. A simplified equivalent circuit replaces the classic bridge. A qualitative analysis of transient processes in the resulting scheme is made. The voltage at the output of the bridge is found using the operator method. The findings have been compared with the simulation model executed in MATLAB/Simulink. The presented method is less labor-intensive than simulation modeling and allows for faster and easier verification of the permissible overvoltage level and oscillation frequency, which is especially important in devices containing a large number of nonlinear elements. It is shown how the parameters of the bridge affect the performance of the transient, in particular the overshoot and oscillation frequency. The attained dependencies are shown in graphical form. The ways of improving the quality of the transition process are given. The findings have been verified on an experimental setup. The obtained theoretical results are consistent with the results of the experiment with the data of other researchers.
A Low-Cost High Performance Electric Vehicle Design Based on Variable Structure Fuzzy PID Control Shamseldin, Mohamed A.; Araby, Medhat; El-khatib, S.
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22071

Abstract

This paper introduces the design steps and implementation of Electric Vehicle (EV) based on variable structure fuzzy PID control. The role of fuzzy logic is making change in the membership function to tune the fuzzy action according to the error and change of error. The control implementation was executed using a low-cost Arduino mega 2560 and had been programed by MATLAB SIMULINK.  Also, a nonlinear model for the EV was built and validated by the actual performance of the EV experimental setup. The overall EV closed loop implemented on the MATLAB SIMULINK to select the proper control parameters. The proposed variable structure fuzzy PID control had been compared to the traditional PID control to ensure robustness and reliability. The results show that the proposed control technique can deal with the EV disturbances and continuous change in the operating points.
Assessment of FLC, PID, Nonlinear PID, and SMC Controllers for Level Stabilization in Mechatronic Systems Al-Samarraie, Shibly A.; Gorial, Ivan I.
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23639

Abstract

Liquid level measurement is a vital task in industries such as food processing, chemical manufacturing, and petroleum. The findings show that FLC and SMC offer superior performance in terms of rapid response, precision, and stability, particularly in handling nonlinear processes. By implementing these sophisticated controllers, industries put up benefit from increased work stability, low material waste, and improved energy efficiency. The study’s results directly contribute to improving industrial applications by optimizing production and minimizing costs. The primary feather objective of a liquid level control system of rules is to exert a predetermined changeable level using a storage tank, measurement system, controller, and pump. This paper compares quaternary controllers: Fuzzy logical system Controller (FLC), Proportional-Integral-Derivative (PID), Nonlinear PID, and Sliding Mode verify (SMC) applied to some I and connected tankful systems. The FLC is an intelligent controller that excels at managing non-linear and uncertain systems by interpreting influx and outflow rates and adjusting the system to maintain desired unstable levels. Its adaptability to undefined scenarios is a key innovation. The PID controller is used as a benchmark undefined to its simplicity simply struggles with non-linear systems and time-varying parameters. The Non-linear PID controller improves upon the traditional PID by using wrongdoing saturation functions, providing better control in non-linear systems. The SMC is a robust control method that ensures system stableness in the front of disturbances and uncertainties, making it highly effective for heavy-duty applications. Simulation results show that FLC and SMC cater a faster response and better accuracy in reaching desired unstable levels compared to traditional PID controllers. Both systems demo robust stableness and efficient control. As seen in the provided data, the FLC reaches a steady-state level in as little as 8.34 seconds in Run 1 and 1.088 seconds in Run 2 for the single-tank system. Similarly, the SMC stabilizes the system in approximately 23.17 seconds in the coupled tank system, reflecting its robust control capabilities.
Enhanced Dynamic Control of Quadcopter PMSMs Using an ILQR-PCC System for Improved Stability and Reduced Torque Ripples Saleh, Ziyaad H.; Mejbel, Basim Ghalib; Radhi, Ahmed Dheyaa; Hashim, Abdulghafor Mohammed; Taha, Taha A.; Gökşenli, Nurettin; Hussain, Abadal-Salam T.; Sekhar, Ravi
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23159

Abstract

Quadcopter technology has developed fast because it’s flexibility and capacity for high maneuvers. What makes PMSM suitable for Quadcopter is their high power to weight ratio, reliability and efficiency. These motors allow the operation of torque and speed control which are important for stability and maneuverability in the flight of the aircraft. Nevertheless, certain and smooth flight caused by regulation of PMSM speed and current is necessary for stable and maneuverable movement. This work presents a new control strategy connecting the ILQR control to govern the speed while the PCC profit the dynamic response and control torque ripples. A comparison is made on the performance of the ILQR-PCC system with nominal Proportional-Integral (PI) control and ILQR.  From the results it is evident that the ILQR-PCC system is far superior to both the PI ILQR controller in regards to the dynamic response, the disturbances rejection capacity as well as reducing the current signal distortions hence reducing the torque ripples. Its working was evidenced in a nonlinear LQR-controlled quadcopter to track the reference accurately and to have minimum distortion in current regulation. The presented work improves the control systems of quadcopters: it introduces a reliable method that improves stability and increases the performance of the quadcopter; therefore, this paper contributes to the existing knowledge.
Cooperative Formation and Obstacle Avoidance Control for Multi-UAV Based on Guidance Route and Artificial Potential Field Sahal, Mochammad; Maynad, Vincentius Charles; Bilfaqih, Yusuf
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23577

Abstract

Research on cooperative control of multi-UAV systems has gained significant attention in the flight control field, with a particular focus on formation control and obstacle avoidance due to their complexity and importance. This paper introduces an approach to a group of quadcopter control by integrating fuzzy controller, guidance route, and Artificial Potential Field (APF) methods. The quadcopter dynamic model, featuring six degrees of freedom, is controlled using a fuzzy state feedback controller in its inner loop. From the outer loop, the formation-making is guided by an easy-to-use and versatile guidance route approach while obstacle avoidance is tackled using the optimal APF method. There are two avoidance strategies that can be compared and analyzed, called "total avoidance" and "minimal avoidance", both individually and as a "combined" strategy. Simulations in various environments with different obstacle sizes show that all control algorithms can accomplish the tasks effectively. Both strategies have their own strength in terms of path length and formation maintenance. A formation performance index, which is calculated based on the difference between the desired position and the actual position of each quadcopter, is used to quantify the effectiveness of the method. A smaller value means better formation maintenance. The total avoidance strategy achieved an average index of 0.8000 and the minimal avoidance strategy reached 1.2227. These metrics highlight the trade-offs of each strategy in maintaining optimal formation. These findings offer valuable insights for the development of more robust multi-UAV systems, with potential applications in autonomous delivery services, surveillance, and environmental monitoring.
Design and Analysis of a Hybrid Intelligent SCARA Robot Controller Based on a Virtual Reality Model Al Mashhadany, Yousif; Abbas, Ahmed K.; Algburi, Sameer; Taha, Bakr Ahmed
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23158

Abstract

SCARA robots have been used in various fields of robotics, such as biomedical engineering, automation, industrial, and gaming. However, our SCARA (Selective Compliance Assembly Robot Arm) VR model stands out with its realistic design and construction assumptions. The VR testing of the robot's motion envelope has facilitated a more precise inverse kinematics solution and verification of the dynamic process. The intelligent controller of this application, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique and a classical proportional-integral-derivative (PID) controller, offers an optimized solution to the accuracy problem. The hybrid ANFIS controller starts with the PID setting parameters of the resultant solution. Following thorough testing of the suggested SCARA manipulator with an intelligent controller in a virtual reality environment, researchers recognized the physical system's potential for implementation utilizing multiple control approaches. Despite the intricacy of its design and implementation, the intelligent controller's software ensures that the system runs at top efficiency. This application replicates the user interface of the MATLAB/SIMULINK var (2022b), which produced promising robotics results, demonstrating its trustworthiness as a realistic, intelligent model, and virtual reality was critical in the development of the SCARA manipulator. It digs into the design and analysis of a hybrid intelligent controller for SCARA robots, which are widely used in assembly lines and manufacturing. Finally, the proposed controller combines the best features of an Adaptive Neuro-Fuzzy Inference System (ANFIS) with a conventional proportional-integral-derivative (PID) controller to resolve application accuracy difficulties as efficiently as possible. 
Enhanced Total Harmonic Distortion Optimization in Cascaded H-Bridge Multilevel Inverters Using the Dwarf Mongoose Optimization Algorithm Salih, Sinan Q.; Mejbel, Basim Ghalib; Ahmad, B. A.; Taha, Taha A.; Bektaş, Yasin; Aldabbagh, Mohammed M; Hussain, Abadal-Salam T.; Hashim, Abdulghafor Mohammed; Radhi, Ahmed Dheyaa
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23548

Abstract

Total harmonic distortion (THD) is one of the most essential parameters that define the operational efficiency and power quality in electrical systems applied to solutions like cascaded H-bridge multilevel inverters (CHB-MLI). The reduction of THD is crucial due to the fact that improving the system’s power quality and minimizing the losses are key for performance improvement. The purpose of this work is to introduce a new DMO-based approach to optimize the THD of the output voltage in a three-phase nine-level CHB-MLI. The proposed DMO algorithm was also subjected to intense comparison with two benchmark optimization techniques, namely Genetic Algorithm and Particle Swarm Optimization with regards to three parameters, namely convergence rate, stability, and optimization accuracy. A series of MATLAB simulations were run to afford the evaluation of each algorithm under a modulation index of between 0.1 and 1.0. The outcome of the experiment amply proves that in comparison with THD minimization for the given OP, the DMO algorithm was significantly superior to both RSA-based GA and PSO algorithms in their ability to yield higher accuracy while requiring lesser computational time. Consequently, this work could expand the application of the DMO algorithm as a reliable and effective means of enhancing THD in CHB-MLIs as well as advancing the overall quality of power systems in different electrical power networks.
Voltage Regulation and Power Management of DC Microgrid with Photovoltaic/Battery Storage System Using Flatness Control Method Mutlag, Ashraf Abdualateef; Abd, Mohommed Kdair; Shneen, Salam Waley
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22530

Abstract

This research aims to propose a power management strategy (PMS) based on the flatness control method for a stand-alone DC microgrid system. The goal of the proposed strategy is to create an efficient PMS using nonlinear flatness theory in order to provide a constant DC bus voltage and the best possible power-sharing mechanism between the battery and the PV array. A maximum power point tracking (MPPT) technique based on an artificial neural network (ANN) to optimize the PV's power. Moreover, the suggested PMS technique was tested in a simulation environment based on MATLAB®/Simulink. The obtained results demonstrate that the proposed PMS method can stabilize the bus voltage under variations in load or solar radiation. Additionally, the PMS method reduced bus voltage spikes and guaranteed good power quality, which extended the battery's lifespan and increased its efficiency. Also, the proposed approach outperforms the standard PI approach in terms of tracking efficiency and has a lower rate of overshoot in the bus voltage under different load scenarios. Therefore, the method is effective when compared with the classical PI approach. The overshoot in the PI method is 58 V, while the overshoot in the DC voltage is 5 V in the proposed method. The tracking speed of the proposed system is very low, and the slower speed was observed in the classical method, and the rise time of PI was 7.9ms, while the proposed method equals 2.2ms.
Application of Sentiment Analysis as an Innovative Approach to Policy Making: A review Firdaus, Asno Azzawagama; Saputro, Joko Slamet; Anwar, Miftahul; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Syuhada, Fahmi; Hidayat, Rahmad
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22573

Abstract

This literature review comprehensively explains the role of sentiment analysis as a policymaking solution in companies, organizations, and individuals. The issue at hand is how sentiment analysis can be effectively applied in decision making. The solution is to integrate sentiment analysis with the latest NLP trends. The contribution of this research is the assessment of 100-200 recent studies in the period 2020-2024 with a sample of more than 5,000 data, as well as the impact of the resulting policy recommendations. The methods used include evaluation of techniques such as Deep Learning, lexicon-based, and Machine Learning, using evaluation matrices such as F1-score, precision, recall, and accuracy. The results showed that Deep Learning techniques achieved an average accuracy of 93.04%, followed by lexicon-based approaches with 88.3% accuracy and Machine Learning with 83.58% accuracy. The findings also highlight the importance of data privacy and algorithmic bias in supporting more responsive and data-driven policymaking. In conclusion, sentiment analysis is reliable in areas such as e-commerce, healthcare, education, and social media for policy-making recommendations. However, special attention should be paid to challenges such as language differences, data bias, and context ambiguity which can be addressed with models such as mBERT, model auditing, and proper tokenization.

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