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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 11 Documents
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Search results for , issue "Vol 4, No 1 (2023)" : 11 Documents clear
Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System Dahmane, Kaoutar; Boulaoutaq, El Mahfoud; Bouachrine, Brahim; Ajaamoum, Mohamed; Imodane, Belkasem; Mouslim, Sana; Benydir, Mohamed
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.16770

Abstract

In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm ???????? and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control.  This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control. 
A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer Aribowo, Widi
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.16445

Abstract

Power system stabilizer (PSS) is applied to dampen system oscillations so that the frequency does not deviate beyond tolerance. PSS parameter tuning is increasingly difficult when dealing with complex and nonlinear systems. This paper presents a novel hybrid algorithm developed from incorporating chaotic maps into the sea-horse optimizer. The algorithm developed is called the chaotic sea-horse optimizer (CSHO). The proposed method is adopted from the metaheuristic method, namely the sea-horse optimizer (SHO). The SHO is a method that duplicates the life of a sea-horse in the ocean when it moves, looks for prey and breeds.  In This paper, The CSHO method is used to tune the power system stabilizer parameters on a single machine system. The proposed method validates the benchmark function and performance on a single machine system against transient response. Several metaheuristic methods are used as a comparison to determine the effectiveness and efficiency of the proposed method. From the research, it was found that the application of the logistics Tent map from the chaotic map showed optimal performance. In addition, the application of the PSS shows effective and efficient performance in reducing overshoot in transient conditions.
Dual Design PID Controller for Robotic Manipulator Application Chotikunnan, Phichitphon; Chotikunnan, Rawiphon
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.16990

Abstract

This research introduces a dual design proportional–integral–derivative (PID) controller architecture process that aims to improve system performance by reducing overshoot and conserving electrical energy. The dual design PID controller uses real-time error and one-time step delay to adjust the confidence weights of the controller, leading to improved performance in reducing overshoot and saving electrical energy. To evaluate the effectiveness of the dual design PID controller, experiments were conducted to compare it with the PID controller using least overshoot tuning by Chien–Hrones–Reswick (CHR)  technique. The results showed that the dual design PID controller was more effective at reducing overshoot and saving electrical energy. A case study was also conducted as part of this research, and it demonstrated that the system performed better when using the dual design PID controller. Overshoot and electrical energy consumption are common issues in systems that can impact performance, and the dual design PID controller architecture process provides a solution to these issues by reducing overshoot and saving electrical energy. The dual design PID controller offers a new technique for addressing these issues and improving system performance. In summary, this research presents a new technique for addressing overshoot and electrical energy consumption in systems through the use of a dual design PID controller. The dual design PID controller architecture process was found to be an effective solution for reducing overshoot and saving electrical energy in systems, as demonstrated by the experiments and case study conducted as part of this research. The dual design PID controller presents a promising solution for improving system performance by addressing the issues of overshoot and electrical energy consumption.
Single Lead EMG signal to Control an Upper Limb Exoskeleton Using Embedded Machine Learning on Raspberry Pi Triwiyanto, Triwiyanto; Caesarendra, Wahyu; Abdullayev, Vugar; Ahmed, Abdussalam Ali; Herianto, Herianto
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.17364

Abstract

Post-stroke can cause partial or complete paralysis of the human limb. Delayed rehabilitation steps in post-stroke patients can cause muscle atrophy and limb stiffness. Post-stroke patients require an upper limb exoskeleton device for the rehabilitation process. Several previous studies used more than one electrode lead to control the exoskeleton. The use of many electrode leads can lead to an increase in complexity in terms of hardware and software. Therefore, this research aims to develop single lead EMG pattern recognition to control an upper limb exoskeleton. The main contribution of this research is that the robotic upper limb exoskeleton device can be controlled using a single lead EMG. EMG signals were tapped at the biceps point with a sampling frequency of 2000 Hz. A Raspberry Pi 3B+ was used to embed the data acquisition, feature extraction, classification and motor control by using multithread algorithm. The exoskeleton arm frame is made using 3D printing technology using a high torque servo motor drive. The control process is carried out by extracting EMG signals using EMG features (mean absolute value, root mean square, variance) further extraction results will be trained on machine learning (decision tree (DT), linear regression (LR), polynomial regression (PR), and random forest (RF)). The results show that machine learning decision tree and random forest produce the highest accuracy compared to other classifiers. The accuracy of DT and RF are of 96.36±0.54% and 95.67±0.76%, respectively. Combining the EMG features, shows that there is no significant difference in accuracy (p-value 0.05). A single lead EMG electrode can control the upper limb exoskeleton robot device well.
Smart Attendance System based on improved Facial Recognition Dang, Thai-Viet
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.16808

Abstract

Nowadays, the fourth industrial revolution has achieved significant advancement in high technology, in which artificial intelligence has had vigorous development. In practice, facial recognition is one most essential tasks in the field of computer vision with various potential applications from security and attendance system to intelligent services. In this paper, we propose an efficient deep learning approach to facial recognition. The paper utilizes the architecture of improved FaceNet model based on MobileNetV2 backbone with SSD subsection.  The improved architecture uses depth-wise separable convolution to reduce the model size and computational volume and achieve high accuracy and processing speed. To solve the problem of identifying a person entering and exiting an area and integrating on advanced mobile devices limits to (such as limited memory and on-device storage) highly mobile resources. Especially, our approach yields better results in practical application with more than 95% accuracy on a small dataset of the original face images. Obtained frame rate (25 FPS) is very favorable compared to the field of facial recognition using neural network. Besides, the deep learning based on solution could be applicable in many low-capacity hardware or optimize system’s resource. Finally, the smart automated attendance systems is successfully designed basing on the improved efficient facial recognition.
Simulation Model of PID Controller for DC Servo Motor at Variable and Constant Speed by Using MATLAB Abdullah, Zainab B.; Shneen, Salam Waley; Dakheel, Hashmia S.
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.15866

Abstract

The current simulation is conducted in order to develop an appropriate design for the control systems and control the speed of the electric motor. To obtain the appropriate and required design, work is carried out for two cases, a constant speed and the other case at variable speed in different conditions for operation of dc servo motor, these conditions include rotating in a clockwise direction, break and returns rotating in the opposite clockwise direction. Through the proposed working conditions, it is possible to obtain the best values for the parameters of the control unit that improve the working performance of dc servo motor, which were shown by the simulation results and their values were kp =5, ki=3 and kd=5 for PID controller. Which changed the system response speed, rise time and the upper and lower bypass ratio at acceptable rates and ratios to prove an improvement procedure in the work of the electric motor.
IoT-Based Smart Air Conditioner as a Preventive in the Post-COVID-19 Era: A Review Saputra, Dhanar Intan Surya; Suarnatha, I Putu Dody; Mahardika, Fajar; Wijanarko, Andik; Handani, Sitaresmi Wahyu
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.17090

Abstract

The Internet of Things (IoT) refers to physical objects with sensors, computing power, software, and other technologies that communicate and exchange data with other devices, platforms, and systems over the Internet or other communication networks. Remarkable developments in IoT have paved the way for new possibilities, enabling the creation and automation of innovative services and advanced applications and constituting a collection of crucial enabling technologies for smart homes. In this New-Normal Era, the concept of an IoT-based Smart Air Conditioner (AC) as a Preventive Effort against COVID-19 is a proposed innovation and application. The Smart AC is designed based on the analysis of existing problems and is equipped with literature obtained in the study. The purpose of this study is to review the research literature on IoT-enabled Smart AC to emphasize the main trends and open problems of integrating IoT technology to create sustainable and efficient Smart homes. The IoT-based Smart AC was designed and equipped with air quality filter features, human sensors, temperature control, voice control, Cloud Storage, and Solar Panel services that can be controlled via smartphone devices. From the framework and study results, the IoT offers many benefits. The IoT-based Smart AC concept is one step ahead of existing AC products.
Modelling and Simulation of a Redundant Agricultural Manipulator with Virtual Prototyping Reddy, A. Sridhar; Chembuly, V. V. M. J. Satish; Rao, V. V. S. Kesava
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.17121

Abstract

The development of autonomous robots for agricultural applications includes motion planning, fruit picking, and collision avoidance with surrounding environments, and these become challenging tasks. For harvesting applications, robust control of the manipulator is needed for the effective motion of the robot. Several combinations of Proportional(P)- Integrative(I)- Derivative(D) controllers are modelled and a simulation study was performed for trajectory tracking of a redundant manipulator in virtual agricultural environments. The article presents a comprehensive study on kinematic modelling and dynamic control of redundant manipulator for fruit-picking applications in virtual environments. The collisions with surrounding environment were eliminated using ‘bounding box technique’. The joint variables are obtained by constructing Inverse Kinematics (IK) problem and are determined using a classical optimization technique. Different controllers are modelled in the ‘Simulink’ environment and are tuned to generate error-free trajectory tracking during harvesting. The task space locations (TSLs) are considered as via-points, and joint variables at each TSLs are obtained by Sequential Quadratic Programming (SQP) technique. Joint-level trajectories are generated using Quintic and B-spline polynomials. For effective trajectory tracking, torque variations are controlled using the PID and Feedforward (FF) controller. The dynamic simulations of the robot manipulator are performed in Simscape Multibody software. Results show that the during the trajectory tracking of the manipulator, the Feed-forward controller performs best with Quintic polynomial trajectory.
Non-Linear Estimation using the Weighted Average Consensus-Based Unscented Filtering for Various Vehicles Dynamics towards Autonomous Sensorless Design Widjiantoro, Bambang L.; Wafi, Moh Kamalul; Indriawati, Katherin
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.16164

Abstract

The concerns to autonomous vehicles have been becoming more intriguing in coping with the more environmentally dynamics non-linear systems under some constraints and disturbances. These vehicles connect not only to the self-instruments yet to the neighborhoods components, making the diverse interconnected communications which should be handled locally to ease the computation and to fasten the decision. To deal with those interconnected networks, the distributed estimation to reach the untouched states, pursuing sensorless design, is approached, initiated by the construction of the modified pseudo measurement which, due to approximation, led to the weighted average consensus calculation within unscented filtering along with the bounded estimation errors. Moreover, the tested vehicles are also associated to certain robust control scenarios subject to noise and disturbance with some stability analysis to ensure the usage of the proposed estimation algorithm. The numerical instances are presented along with the performances of the control and estimation method. The results affirms the effectiveness of the method with limited error deviation compared to the other centralized and distributed filtering. Beyond these, the further research would be the directed sensorless design and fault-tolerant learning control subject to faults to negate the failures.
Design of Multivariate PID Controller for Power Networks Using GEA and PSO Zadehbagheri, Mahmoud; Ma'arif, Alfian; Ildarabadi, Rahim; Ansarifard, Mehdi; Suwarno, Iswanto
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.15682

Abstract

The issue of proper modeling and control for industrial systems is one of the challenging issues in the industry. In addition, in recent years, PID controller design for linear systems has been widely considered. The topic discussed in some of the articles is mostly speed control in the field of electric machines, where various algorithms have been used to optimize the considered controller, and always one of the most important challenges in this field is designing a controller with a high degree of freedom. In these researches, the focus is more on searching for an algorithm with more optimal results than others in order to estimate the parameters in a more appropriate way. There are many techniques for designing a PID controller. Among these methods, meta-innovative methods have been widely studied. In addition, the effectiveness of these methods in controlling systems has been proven. In this paper, a new method for grid control is discussed. In this method, the PID controller is used to control the power systems, which can be controlled more effectively, so that this controller has four parameters, and to determine these parameters, the optimization method and evolutionary algorithms of genetics (EGA) and PSO are used.  One of the most important advantages of these algorithms is their high speed and accuracy. In this article, these algorithms have been tested on a single-machine system, so that the single-machine system model is presented first, then the PID controller components will be examined. In the following, according to the transformation function matrix and the relative gain matrix, suitable inputs for each of the outputs are determined. At the end, an algorithm for designing PID controller for multivariable MIMO systems is presented. To show the effectiveness of the proposed controller, a simulation was performed in the MATLAB environment and the results of the simulations show the effectiveness of the proposed controller.

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