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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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Optimization of an Autonomous Mobile Robot Path Planning Based on Improved Genetic Algorithms Abu, N. S.; Bukhari, W. M.; Adli, M. H.; Ma’arif, Alfian
Journal of Robotics and Control (JRC) Vol 4, No 4 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i4.19306

Abstract

Mobile robots are intended to operate in a variety of environments, and they need to be able to navigate and travel around obstacles, such as objects and barriers. In order to guarantee that the robot will not come into contact with any obstacles or other objects during its movement, algorithms for path planning have been demonstrated. The basic goal while constructing a route is to find the fastest and smoothest route between the starting point and the destination. This article describes route planning using the improvised genetic algorithm with the Bezier Curve (GA-BZ). This study carried out two main experiments, each using a 20x20 random grid map model with varying percentages of obstacles (5%, 15%, and 30% in the first experiment, and 25% and 50% in the second). In the initial experiments, the population (PN), generation (GN), and mutation rate (MR) of genetic algorithms (GA) will be altered to the following values: (PN = 100, 125, 150, or 200; GN = 100, 125, 150; and MR = 0.1, 0.3, 0.5, 0.7) respectively. The goal is to evaluate the effectiveness of AMR in terms of travel distance (m), total time (s), and total cost (RM) in comparison to traditional GA and GA-BZ. The second experiment examined robot performance utilising GA, GA-BZ, Simulated Annealing (SA), A-Star (A*), and Dijkstra's Algorithms (DA) for path distance (m), time travel (s), and fare trip (RM). The simulation results are analysed, compared, and explained. In conclusion, the project is summarised.
Comparison of Spider-Robot Information Models Kravchenko, Viktor V.; Efremov, Artem A.; Zhilenkov, Anton A.; Kozlov, Vladimir N.; Silkin, Artem A.; Moiseev, Ilya S.; Krupinin, Oleg; Lebedeva, Ekaterina
Journal of Robotics and Control (JRC) Vol 4, No 5 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i5.19533

Abstract

The paper deduces a mathematical model of a spider-robot with six three-link limbs. Many limbs with a multi-link structure greatly complicate the process of synthesizing a model, since in total the robot has twenty-four degrees of freedom, i.e., three coordinates of the center of mass of the body in space, three angles of rotation of the body relative to its center of mass and three degrees of freedom for each limb, to describe the position of the links. The derived mathematical model is based on the Lagrange equations with a further transformation of the equations to the Cauchy normal form in a matrix form. To test the resulting model in a SimInTech environment, an information model is synthesized and two simple experiments ar carried out to simulate the behavior of real spiders: moving forward in a straight line and turning in place at a given angle. The experimental results demonstrate that the synthesized information model can well cope with the tasks and the mathematical model underlying it can be used for further research.
Optimum PID Controller with Fuzzy Self-Tuning for DC Servo Motor Abdelghany, M. A.; Okasha Elnady, Abdelrady; Ibrahim, Shorouk Ossama
Journal of Robotics and Control (JRC) Vol 4, No 4 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i4.18676

Abstract

DC motors are simple and controllable, making them a popular choice for various applications. However, the speed and load characteristics of DC motors can change, making it difficult to control them effectively. This paper proposes an optimum PID controller with fuzzy self-tuning for DC servo motors. The controller uses two steps to adjust the PID gains: The ACS algorithm is employed to identify the optimal PID gains in the first step. A fuzzy logic (FLC) controller is employed in the second stage to further fine-tune the gains. The FLC considers two cost functions: the first function is the sum of the squares of the error between the controlled output and reference input. The second function is a mathematical expression that specifies the required characteristics of the system response. The fuzzy self-tune then uses a set of rules to adjust the PID gains in response to changes in the system. The rules are based on the two cost functions designed to maintain the optimum PID gains for various operating settings. The outcomes of the two functions are: Kp = 5.2381, Ki = 7.0427, and Kd = 0.49468, with rising time = 0.2503, overshoot = 2.5079, and settling time = 10.4824 in the first cost function. The second cost function outcomes are Kp = 8.1381; Ki = 8.6427; and Kd = 0.49468. The FST-PID controller's performance is evaluated using Matlab-Simulink. The proposed controller was tested on a DC servo motor, and the results showed good performance in both steady-state and transient responses. The controller also maintained the optimum PID gains in the event of changes or disturbances. So, the motor's speed can effectively control under a variety of conditions.
Urinary Tract Infection Bacteria Classification: Artificial Intelligence-based Medical Application Fadlil, Abdul; Fathurrahman, Haris Imam Karim; Lin, Yu-Hao; Kamilah, Farhah; Sunardi, Sunardi
Journal of Robotics and Control (JRC) Vol 4, No 5 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i5.18879

Abstract

Urinary tract infection (UTI) is a type of health disorder, an infection in the urinary glands mainly caused by bacteria. Currently, conventional early detection methods that have been established involve rapid dipstick strip test and urine culture analysis, which have suboptimal accuracy and effectiveness. Several retrospective studies regarding UTI bacteria classification have shown promising results, but still have limitations regarding prediction accuracy and technical simplicity. This study aims to implement a method based on artificial intelligence (AI) in classifying images of bacteria that causes UTIs. Eight artificial intelligence methods based on deep neural networks were used in the study; the models were evaluated and compared based on the prediction's effectiveness and accuracy. This study also seeks to create the easiest method of classifying bacteria causing UTIs using a computer-based application with the best obtained AI-based model. The best training results using an intelligent approach placed DenseNet201 as the method with the highest accuracy (83.99%). Then, the output model was used as a knowledge reference for the designed computer-based application. Real-time prediction results will appear in the application window.
Application of Machine Learning in Healthcare and Medicine: A Review Furizal, Furizal; Ma'arif, Alfian; Rifaldi, Dianda
Journal of Robotics and Control (JRC) Vol 4, No 5 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i5.19640

Abstract

This extensive literature review investigates the integration of Machine Learning (ML) into the healthcare sector, uncovering its potential, challenges, and strategic resolutions. The main objective is to comprehensively explore how ML is incorporated into medical practices, demonstrate its impact, and provide relevant solutions. The research motivation stems from the necessity to comprehend the convergence of ML and healthcare services, given its intricate implications. Through meticulous analysis of existing research, this method elucidates the broad spectrum of ML applications in disease prediction and personalized treatment. The research's precision lies in dissecting methodologies, scrutinizing studies, and extrapolating critical insights. The article establishes that ML has succeeded in various aspects of medical care. In certain studies, ML algorithms, especially Convolutional Neural Networks (CNNs), have achieved high accuracy in diagnosing diseases such as lung cancer, colorectal cancer, brain tumors, and breast tumors. Apart from CNNs, other algorithms like SVM, RF, k-NN, and DT have also proven effective. Evaluations based on accuracy and F1-score indicate satisfactory results, with some studies exceeding 90% accuracy. This principal finding underscores the impressive accuracy of ML algorithms in diagnosing diverse medical conditions. This outcome signifies the transformative potential of ML in reshaping conventional diagnostic techniques. Discussions revolve around challenges like data quality, security risks, potential misinterpretations, and obstacles in integrating ML into clinical realms. To mitigate these, multifaceted solutions are proposed, encompassing standardized data formats, robust encryption, model interpretation, clinician training, and stakeholder collaboration.
Nonlinear Cascaded Control for a DC-DC Boost Converter Mansouri, Amirhosein; Gavagsaz-Ghoachani, Roghayeh; Phattanasak, Matheepot; Pierfederici, Serge
Journal of Robotics and Control (JRC) Vol 4, No 4 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i4.18932

Abstract

The Boost Converter is a type of DC-DC converter that operates using switching techniques and is designed to elevate the voltage level. This paper presents a cascaded control for a boost converter to ensure that the inductor current and output capacitor voltage remain in a safe operating zone. Ensuring safe operating conditions and stable closed-loop poles is crucial because it guarantees that both current and voltage remain within the designated operating range. This preventive measure prevents any damage to components like capacitors (C), inductors (L), and switches. Unstable operation, on the other hand, could lead to oscillations and an undesirable increase in the amplitude of current and voltage, posing a risk to all components involved. The research contribution involves an investigation of cascaded control, utilizing power and energy concepts due to their advantageous effects on system performance and design. By implementing nonlinear controllers based on a large-signal averaged model, the closed-loop poles remain independent of operating points, eliminating the need for small-signal linearization. Small-signal linearization makes the controlled system dependent on the operating point. Two controllers are introduced based on power and energy concept, which is easy to understand. The potential practical application of the proposed cascaded control approach is in high-power applications. Tracking the energy stored in the output capacitor is first investigated to validate the proposed control scheme by varying the output voltage reference from 32 V to 50 V. Then, the regulation of the energy voltage is explored by varying the load resistance for the output voltage at 50 V. Both are done using a switched model using MATLAB/Simulink software. Simulation results are given to demonstrate the effectiveness of the proposed method. The key metrics used to assess the effectiveness of the proposed control scheme are the undershoot voltage and robustness. The results show that the studied system's tracking, regulating operations and robustness properties are as expected. The proposed method faces a challenge with the number of sensors required. To address this, observers can be utilized to reduce sensor usage while maintaining measurement accuracy. The proposed method can be applied to other power electronic systems.
A Novel Hybrid Prairie Dog Optimization Algorithm - Marine Predator Algorithm for Tuning Parameters Power System Stabilizer Aribowo, Widi; Rohman, Miftahur; Baskoro, Farid; Harimurti, Rina; Yamasari, Yuni; Yustanti, Wiyli
Journal of Robotics and Control (JRC) Vol 4, No 5 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i5.19521

Abstract

The article presents the parameter tuning of the Power System Stabilizer (PSS) using the hybrid method. The hybrid methods proposed in this article are Praire Dog Optimization (PDO) and Marine Predator Algorithm (MPA). The proposed method can be called PDOMPA. In the PDOMPA method, the marine predator algorithm (MPA) is able to search around optimal individuals when updating population positions. MPA is used to make the exploration and exploitation stages of PDO more valid and accurate. PDO is an algorithm inspired by the life of prairie dogs. Prairie dogs are adapted to colonizing in burrows underground. Prairie dogs have daily habits of eating, observing for predators, establishing fresh burrows, or preserving existing ones. Meanwhile, MPA is a duplication of marine predator life which is modeled mathematically. In order to validate the performance of the PDOMPA method, this article presents a comparative simulation of the objective function and the transient response of PSS. This research uses validation by comparing with conventional methods, Whale Optimization Algorithm (WOA), Grasshopper Optimization Algorithm (GOA), Marine Predator Algorithm (MPA), and Praire Dog Optimization (PDO). Based on the simulation results, PDOMPA presents fast convergence in some cases and shows optimal results compared to competitive algorithms. From the simulation results using load variations, it was found that the proposed method has the ability to reduce the average undershoot and overshoot of speed by 42.2% and 85.37% compared to the PSS-Lead Lag method. Meanwhile the average settling time value of speed is 50.7%.
Real-Time Inverse Dynamic Deep Neural Network Tracking Control for Delta Robot Based on a COVID-19 Optimization Shamseldin, Mohamed
Journal of Robotics and Control (JRC) Vol 4, No 5 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i5.18865

Abstract

This paper presents a new technique to design an inverse dynamic model for a delta robot experimental setup to obtain an accurate trajectory. The input/output data were collected using an NI DAQ card where the input is the random angles profile for the three-axis and the output is the corresponding measured torques. The inverse dynamic model was developed based on the deep neural network (NN) and the new COVID-19 optimization to find the optimal initial weights and bias values of the NN model. Due to the system uncertainty and nonlinearity, the inverse dynamic model is not enough to track accurately the preselected profile. So, the PD compensator is used to absorb the error deviation of the end effector. The experimental results show that the proposed inverse dynamic deep NN with PD compensator achieves good performance and high tracking accuracy. The suggested control was examined using two different methods. The spiral path is the first, with a root mean square error of 0.00258 m, while the parabola path is the second, with a root mean square error of 0.00152 m.
Investigation of Optimal Controllers on Dynamics Performance of Nonlinear Active Suspension Systems with Actuator Saturation Al-Ali, Mohammed A.; Lutfy, Omar F.; Al-Khazraj, Huthaifa
Journal of Robotics and Control (JRC) Vol 5, No 4 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i4.22139

Abstract

This study investigates designing optimal controllers on the dynamics performance of active suspension systems. The study incorporates nonlinearities and actuator saturation in the mathematical model of the suspension system for more reasonable representation of the real system. To improve ride comfort and stability performance in the presence of road disturbances, this study proposes two control frameworks including the Proportional-Integral-Derivative (PID) controller and the State Feedback (SF) controller. The focus of the study is to overcome the limitations of existing approaches in handling the actuator saturation in the controller design. To attain a better performance of the two proposed controllers including the input control constraint, a Grey Wolf Optimization (GWO) has been introduced to improve the searching process for the optimal values of the controllers’ adjustable parameters. The simulation results using MATLAB show that the proposed controllers exhibit a good performance in normal operation and in a robustness test involving system parameters’ changes. In terms of improving the response of the system, the GWO-PID controller shows a better response than that of the GWO-SF controller. Based on the Integral Square Error (ISE) index, the ISE is reduced by 16.67% using the GWO-PID controller compared to the GWO-SF controller.
Design and Develop a Non-Invasive Pulmonary Vibration Device for Secretion Drainage in Pediatric Patients with Pneumonia Wongkamhang, Anantasak; Wuttipan, Nathamon; Chotikunnan, Rawiphon; Roongprasert, Kittipan; Chotikunnan, Phichitphon; Thongpance, Nuntachai; Sangworasil, Manas; Srisiriwat, Anuchart
Journal of Robotics and Control (JRC) Vol 4, No 5 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i5.19588

Abstract

The study aimed to develop a non-invasive pulmonary vibration device, specifically tailored for pediatric patients, to address a range of pulmonary conditions. The device employs a PID control system to ensure consistent and precise vibrations. The primary contribution of this research is the successful development, testing, and implementation of this innovative device. Utilizing technical components such as an Arduino, a vibration DC motor, and an ADXL335 accelerometer, the device was engineered to deliver stable and continuous vibrations even when subjected to external pressures or interactions with the patient. Controllers, including P, PI, PD, and PID types, were rigorously compared. The Ziegler-Nichols tuning technique was applied for meticulous evaluation of vibration control specifically within the context of this non-invasive pulmonary vibration device. Our findings revealed that the PID controller displayed superior accuracy in vibration control compared to P, PI, and PD controllers. Clinical trials involving pediatric patients showed that the PID-controlled device achieved treatment outcomes comparable to conventional methods. The device's precise control of vibration strength provides an added benefit, making it a well-tolerated, non-invasive treatment option for various pulmonary conditions in pediatric patients. Future research is necessary to assess the long-term effectiveness of the device and to facilitate its integration into standard clinical practice. In summary, this study represents a significant advancement in pediatric pulmonary care, demonstrating the critical role that PID control systems adapted for non-invasive pulmonary vibration devices can play in enhancing treatment precision and outcomes.

Page 39 of 71 | Total Record : 708

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