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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 35 Documents
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Search results for , issue "Vol. 5 No. 6 (2024)" : 35 Documents clear
Formation Control of Multiple Unmanned Aerial Vehicle Systems using Integral Reinforcement Learning Dang, Ngoc Trung; Duong, Quynh Nga
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.v5i6.23505

Abstract

Formation control of Unmanned Aerial Vehicles (UAVs), especially quadrotors, has many practical applications in contour mapping, transporting, search and rescue. This article solves the formation tracking requirement of a group of multiple UAVs by formation control design in outer loop and integral Reinforcement Learning (RL) algorithms in position sub-system. First, we present the formation tracking control structure, which uses a cascade description to account for the model separation of each UAV. Second, based on value function of inner model, a modified iteration algorithm is given to obtain the optimal controller in the presence of discount factor, which is necessary to employ due to the finite requirement of infinite horizon based cost function. Third, the integral RL control is developed to handle dynamic uncertainties of attitude sub-systems in formation UAV control scheme with a discount factor to be employed in infinite horizon based cost function. Specifically, the advantage of the proposed control is pointed out in not only formation tracking problem but also in the optimality effectiveness. Finally, the simulation results are conducted to validate the proposed formation tracking control of a group of multiple UAV system.
Work Fatigue Detection of Search and Rescue Officers Based on Hjorth EEG Parameters Pamungkas, Yuri; Indriani, Ratri Dwi; Crisnapati, Padma Nyoman; Thwe, Yamin
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.v5i6.23511

Abstract

Work fatigue can cause a decrease in cognitive function, such as decreased thinking ability, concentration, and memory. A tired brain cannot work optimally, interfering with a person's ability to perform tasks that require complex thinking. In general, to evaluate work fatigue in a person, self-assessment activities using the Perceived Stress Scale (PSS) are the method most often used by researchers or practitioners. However, this method is prone to bias because sometimes people try to hide or exaggerate their tiredness at work. Therefore, we propose to evaluate people's work fatigue based on their EEG data in this study. A total of 25 participants from SAR officers recorded their EEG data in relaxed conditions (pre-SAR operations) and fatigue conditions (post-SAR operations). Recording was performed on the brain's left (fp1 & t7) and right (fp2 & t8) hemispheres. The EEG data is then processed by filtering, artifact removal using ICA method, signal decomposition into several frequency bands, and Hjorth feature extraction (activity, mobility, and complexity). The main advantage of Hjorth parameters compared to other EEG features is its ability to provide rich information about the complexity and mobility of the EEG signal in a relatively simple and fast way. Based on the results of activity feature extraction, feature values will tend to increase during the post-SAR operation conditions compared to the pre-operation SAR conditions. In addition, the results of the classification of pre-and post-operative SAR conditions using Bagged Tree algorithm (10-fold cross validation) show that the highest accuracy can be obtained is 94.8%.
Enhancing Autonomous Navigation in GNSS-Denied Environment: Obstacle Avoidance Observability-Based Path Planning for ASLAM Elahian, Samaneh; Atashgah, Mohammad Ali Amiri; Suwarno, Iswanto
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.v5i6.23519

Abstract

Obstacle avoidance (OA) is necessary for any path planning in outdoor environment to prevent any collision with the obstacles in natural environment. In this paper, a quadrotor navigates using Active Simultaneously Localization and Mapping (ASLAM) in GNSS-denied outdoor environment. In ASLAM, the quadrotor path is defined using real-time Observability Based Path Planning (OBPP) method, autonomously. To prepare using of the OBPP in outdoor environment, it is necessary to add the ability of OA to it. So, the OA-OBPP method is introduced which defines the path based on terrestrial landmarks while preventing any collision with the obstacles. This approach is developed by redefining a dataset of in range landmarks while all of the landmark in the vicinity of the obstacles are removed from the in-range landmarks dataset.  To evaluate the performance of the proposed method, simulations of the OA-OBPP algorithm are conducted for a simplified 6-Degree of Freedom (DOF) quadrotor using MATLAB. The simulations evaluate the efficiency, accuracy and robustness of the proposed method. Results across various scenarios show that the method effectively avoids collisions with obstacles while simultaneously determining a path to the goal. Additionally, a comparison of the position estimation RMSE with Monte Carlo PP highlights the accuracy of the OA-OBPP. The robustness of the method, tested with varying initial positions, demonstrates its success in real-time path planning (PP) from any starting point to the destination without collisions. The results confirm that the OA-OBPP enhances the robot's capability to perform real-time, autonomous, and robust path planning in outdoor environments, even in the absence of GNSS signals, through visual navigation.
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; Veena, B. 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.v5i6.23548

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.
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.
Combining Finite State Machine and Fuzzy Logic Control for Accuracy Enhancing Performance of a Tomato-Handling Robot Gripper Mardiati, Rina; Firdaus, Hardiansyah; Setiawan, Aan Eko; Zulherman, Dodi
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.v5i6.23579

Abstract

Robotic grippers are becoming increasingly vital in modern agriculture, especially in tasks like harvesting delicate crops such as tomatoes, where precision and care are crucial. These advanced tools are designed to handle tomatoes without causing damage, significantly improving efficiency and reducing labor costs. Research on gripper robots for fruit picking continues to be developed using various methods in an effort to achieve accurate picking results. This study proposes a hybrid method that combines Finite State Machine (FSM) for behavior control with Fuzzy Logic Control (FLC) to optimize the positioning of the gripper. The system utilizes a PixyCam2 CMUcam5 for tomato detection, an Arduino microcontroller for image processing, and a servo mechanism to precisely align the gripper with the target. The experimental results confirm that each component functions as expected, with the gripper successfully performing actions such as idling, gripping, and placing in accordance with the FSM model. Furthermore, the FLC model was tested against simulations, resulting in error rates of 1.004% for the elbow angle and 0.826% for the base angle. The entire system was validated by comparing the performance of the system using FLC and non-FLC in ten tests, each with tomatoes placed in different positions. The results indicate that the proposed gripper, utilizing the FSM-FLC model, achieved a 100% success rate in grasping the target, significantly outperforming the FSM-non-FLC gripper, which achieved only a 20% success rate. These findings have important implications for the agricultural industry. The successful integration of the FSM and FLC models in robotic grippers paves the way for fully automated harvesting systems, potentially reducing costs and enhancing productivity.
Model-free Optimal Control for Underactuated Quadrotor Aircraft via Reinforcement Learning Duong, Quynh Nga; Dang, Ngoc Trung
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.v5i6.23585

Abstract

The control of Unmanned Aerial Vehicles (UAVs), especially quadrotor aircraft, has many practical applications such as transporting, mapping, rescue, and agricultural applications. This paper investigates solving the optimal tracking control problem for a quadrotor system. First, an underactuated quadrotor system is considered a highly nonlinear system with six degrees of freedom and four inputs. Second, a hierarchical control structure consisting of position and attitude controller is adopted to address the underactuated problem, the position controller to achieve the desired tracking and generates the references for the attitude controller, and the attitude controller to achieve the reference attitude tracking. Third, to achieve optimal trajectory tracking, two Data- based Reinforcement Learning (RL) algorithms are applied to both position and attitude controllers to find the optimal control input by using the input- output quadrotor system data. Compared with the traditional optimal algorithms which require directly solving the Algebraic Ricatti Equation (ARE) or the Hamilton-Jacobi-Bellman (HJB) equation. It is impossible or difficult to implement due to the high nonlinear dynamic nature of the quadrotor system. By using RL in the proposed method, optimal policies can be learned without the knowledge of quadrotor dynamic information. Applying the learning control policies to the quadrotor system, the vehicle achieves optimal trajectory tracking. Finally, a simulation result is conducted to verify the optimal trajectory tracking for quadrotor with the proposed controller.
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.
Optimal Integral Sliding Mode Controller Design for Micro Gyroscope Based on Time Delay Estimation Faraj, Mohammad A.; Jassam, Sameh; Abbas, Ahmed K.
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.v5i6.23676

Abstract

Controlling Micro-Electro-Mechanical Systems (MEMS) gyroscopes often involves dealing with uncertainties and external disturbances, which can complicate control strategies. This article proposes a novel control strategy that integrates Integral Sliding Mode Control (ISMC) with Time Delay Estimation (TDE) and Arithmetic Optimization Algorithm (AOA) to enhance control performance. The proposed controller, OTDISMC, is designed to eliminate chattering and improve robustness against disturbances without relying on system dynamics. Contrary to the conventional controllers structures which depended on the system dynamic in their schemes, a model free controller is formulated without using system dynamics in its formulation. Time delay estimation technique has been undertaken as an efficient approximating strategy to approximate and compensate the lumped uncertain dynamics of the system. AOA has been undertaken to determine the optimum solutions of the coefficients of proposed control approach. The stability has been analyzed and investigated using the Lyapunov stability criterion. To show the effectiveness and validity of the developed controller, computer simulations in nominal and robustness scenarios have been carried out and compared with TDISMC that tuned by trial and error and PSO-TDISMC that tuned by particle swarm optimization (PSO). Simulation results demonstrate that OTDISMC significantly reduces tracking errors and improves robustness. The results indicate the superiority of the proposed controller as compared with traditional TDISMC tuned by classical methods and PSO-TDISMC tuned by particle swarm optimization (PSO).
Evaluation of Voltage/Frequency and Voltage Source Inverter Control Strategies for Single-Phase Induction Motors Using MATLAB Simulation Dakheel, Hashmia S.; Shneen, Salam Waley; Abdullah, Zainab B.; Shuraiji, Ahlam Luaibi
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.v5i6.23760

Abstract

There is a growing interest in studying the single-phase induction motor due to its wide use in many applications, the most important of which are domestic and industrial. A simulation model is built by implementing and running the model using MATLAB to identify the system behavior of the induction motor. To study and analyze the system behavior in different cases, it is proposed to implement and run the model in two ways: the first without control techniques and the second using control techniques. Tests are conducted according to a methodology based on scenarios that include all expected cases that can be assumed to suit real-time operation. To evaluate control strategies, the clear effect between their use and non-use must be demonstrated through clear measurement criteria to include response speed and performance improvement. In induction motor tests, the focus is on electrical and mechanical quantities and the transient and steady state of the system, including a 220-volt supply voltage and a 50 Hz frequency. The initial test case refers to using the model to simulate three cases: the first without load, the second with a constant load of one newton meter, and the third operating the motor as a pump by changing the load according to the pumping quantity and linked to the motor output. After conducting these tests, the different simulation results can be indicated in terms of the change in electrical and mechanical quantities over time during the proposed operating period. The results showed the high starting current that may affect the motor, and the response time for the motor to operate at the rated speed can be considered. Therefore, this requires the use of techniques to improve performance and provide response speed with a gradual increase in the starting current to protect the motor from high starting current. Voltage and frequency control techniques, as well as voltage-to-frequency ratio and another technique representing the voltage source inverter, were used. The results indicate a clear improvement through the stability of the motor by operating with a short response time compared to other cases and the specified rotational speed and specified torque, which shows a relatively high-efficiency performance.

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