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
11 Documents
Search results for
, issue
"Vol 4, No 2 (2023)"
:
11 Documents
clear
<![CDATA[Flower Pollination Algorithm to Tune PID Controller of TCP/AQM Wireless Networks ]]>
<![CDATA[Eissa, Suad Ali]]>;
<![CDATA[Shneen, Salam Waley]]>;
<![CDATA[Ali, Ekbal Hussain]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17533
<![CDATA[The current study aims to conduct a simulation that is useful in developing an appropriate design that addresses the problem of congestion in the Internet network through controlling the queue of the router. The simulation is conducted through the proposed model for simulation with different control systems that help in raising the quality of performance such as traditional Proportional Integral Derivative (PID) and advanced optimal by Flower Pollination Algorithm (FPA). It depends for Transmission Control Protocol/ Active Queue Management( TCP/AQM )simulation model for a linear system and another non-linear system. To adjust the network work and raise the level of performance, different control systems were chosen, taking into account all the things that appear through conducting experiments and for different purposes. One of the most important things that must be taken into consideration is the system disturbances as a result of the volume and values of the data, causing congestion . It was shown through the results of the experiments that were conducted considering the cases of the linear and nonlinear system to pass data traffic in the network and by adopting the different techniques of the control units, the preference of optimizasion systems over the traditional ones, as well as the preference of the traditional over without control in close loop, is the improvement of the performance of linear systems compared to the open and closed system without control. The simulation results showed that very clear the superiority of the optimization by FPA-PID controller over the conventional system (PID) , as well as very clear the superiority of the traditional system (PID)over closed system without control and open loop system.]]>
<![CDATA[A New Self-Tuning Nonlinear PID Motion Control for One-Axis Servomechanism with Uncertainty Consideration ]]>
<![CDATA[Shamseldin, Mohamed A.]]>;
<![CDATA[Abdelghany, Mohamed A.]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17433
<![CDATA[This paper introduces a new study for one-axis servomechanism with consideration the parameter variation and system uncertainty. Also, a new approach for high-performance self-tuning nonlinear PID control was developed to track a preselected profile with high accuracy. Moreover, a comparison study between the proposed control technique and the well-known controllers (PID and Nonlinear PID). The optimal control parameters were determined based on the COVID-19 optimization technique. The parameters of the servomechanism system changed randomly at a preselected range through the online simulation. The change of these parameters acts as the nonlinearity resources (friction, backlash, environmental effects) and system uncertainty. A comparative study between the linear and nonlinear models had been accomplished and investigated. The results show that the proposed controller can track several operating points with high accuracy, low rise time, and small overshoot.]]>
<![CDATA[Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application ]]>
<![CDATA[Chotikunnan, Phichitphon]]>;
<![CDATA[Pititheeraphab, Yutthana]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17757
<![CDATA[This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance.]]>
<![CDATA[Path Following and Avoiding Obstacle for Mobile Robot Under Dynamic Environments Using Reinforcement Learning ]]>
<![CDATA[Hanh, Le Duc]]>;
<![CDATA[Cong, Vo Duy]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17368
<![CDATA[Obstacle avoidance for mobile robot to reach the desired target from a start location is one of the most interesting research topics. However, until now, few works discuss about working of mobile robot in the dynamic and continuously changing environment. So, this issue is still the research challenge for mobile robots. Traditional algorithm for obstacle avoidance in the dynamic, complex environment had many drawbacks. As known that Q-learning, the type of reinforcement learning, has been successfully applied in computer games. However, it is still rarely used in real world applications. This research presents an effectively method for real time dynamic obstacle avoidance based on Q-learning in the real world by using three-wheeled mobile robot. The position of obstacles including many static and dynamic obstacles and the mobile robot are recognized by fixed camera installed above the working space. The input for the robot is the 2D data from the camera. The output is an action for the robot (velocities, linear and angular parameters). Firstly, the simulation is performed for Q-learning algorithm then based on trained data, The Q-table value is implemented to the real mobile robot to perform the task in the real scene. The results are compared with intelligent control method for both static and dynamic obstacles cases. Through implement experiments, the results show that, after training in dynamic environments and testing in a new environment, the mobile robot is able to reach the target position successfully and have better performance comparing with fuzzy controller.]]>
<![CDATA[Obstacle Avoidance Based on Stereo Vision Navigation System for Omni-directional Robot ]]>
<![CDATA[Umam, Faikul]]>;
<![CDATA[Fuad, Muhammad]]>;
<![CDATA[Suwarno, Iswanto]]>;
<![CDATA[Ma'arif, Alfian]]>;
<![CDATA[Caesarendra, Wahyu]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17977
<![CDATA[This paper addresses the problem of obstacle avoidance in mobile robot navigation systems. The navigation system is considered very important because the robot must be able to be controlled from its initial position to its destination without experiencing a collision. The robot must be able to avoid obstacles and arrive at its destination. Several previous studies have focused more on predetermined stationary obstacles. This has resulted in research results being difficult to apply in real environmental conditions, whereas in real conditions, obstacles can be stationary or moving caused by changes in the walking environment. The objective of this study is to address the robot’s navigation behaviors to avoid obstacles. In dealing with complex problems as previously described, a control system is designed using Neuro-Fuzzy so that the robot can avoid obstacles when the robot moves toward the destination. This paper uses ANFIS for obstacle avoidance control. The learning model used is offline learning. Mapping the input and output data is used in the initial step. Then the data is trained to produce a very small error. To support the movement of the robot so that it is more flexible and smoother in avoiding obstacles and can identify objects in real-time, a three wheels omnidirectional robot is used equipped with a stereo vision sensor. The contribution is to advance state of the art in obstacle avoidance for robot navigation systems by exploiting ANFIS with target-and-obstacles detection based on stereo vision sensors. This study tested the proposed control method by using 15 experiments with different obstacle setup positions. These scenarios were chosen to test the ability to avoid moving obstacles that may come from the front, the right, or the left of the robot. The robot moved to the left or right of the obstacles depending on the given Vy speed. After several tests with different obstacle positions, the robot managed to avoid the obstacle when the obstacle distance ranged from 173 – 150 cm with an average speed of Vy 274 mm/s. In the process of avoiding obstacles, the robot still calculates the direction in which the robot is facing the target until the target angle is 0.]]>
<![CDATA[Development of a Virtual Environment-Based Electrooculogram Control System for Safe Electric Wheelchair Mobility for Individuals with Severe Physical Disabilities ]]>
<![CDATA[Ogenga, Jane Phoebe Achieng]]>;
<![CDATA[Njeri, Paul Waweru]]>;
<![CDATA[Muguro, Joseph Kamau]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17165
<![CDATA[Conventional wheelchairs are predominantly manual or joystick-operated electric wheelchairs. However, operating these wheelchairs can be difficult or impossible for individuals with severe physical disabilities. Due to losing control of their physical limbs, they depend on an attendant for assistance. As a remedy, bio-signals may be used as a control mechanism since they are readily available and can be acquired from any body part. This research proposes to use EOG signals to vail a control mechanism and test it in a virtual and actual electric wheelchair. The main contribution of the study is an investigation of the use of EOG to control an electric wheelchair in a virtual environment to determine safe control parameters for wheelchair use in complex environments. A customized data acquisition circuit was developed to acquire single-channel EOG signals using wet electrodes. The acquired signal was filtered and processed using feature extraction and classification techniques in MATLAB software. Two customized control environments were developed in Unity 3D, one with equally partitioned sections and the other with sections decreasing in size as the robot wheelchair approaches the target. Twenty-two test subjects (mean age 24.5, std 1.5) participated in the study, controlling the robot wheelchair in real-time with non or least instances of collision and oversteering. The system achieved an accuracy of 96.5% with a response time of 0.7s, translating to an ITR of 70.6 bits/min. Overall, the participants managed to navigate the virtual environment with a completion time of 101.94s ± 19.71 and 109.07s ± 13.25 for the male and female participants, respectively. In the scene with decreasing section sizes, 72% and 54% instances of collision and oversteering were reported, respectively, highlighting the need to consider the complexity of the control environment and the sufficiency of the participants' control skills to ensure safety in operations. The results confirm the usefulness of EOG as a control interface, with little or no need for recalibration. It provides a promising avenue for individuals with severe physical disabilities to operate wheelchairs independently in complex environments, enhancing their quality of life.]]>
<![CDATA[Validation of Quad Tail-sitter VTOL UAV Model in Fixed Wing Mode ]]>
<![CDATA[Priyambodo, Tri Kuntoro]]>;
<![CDATA[Majid, Abdul]]>;
<![CDATA[Shouran, Zaied Saad Salem]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17253
<![CDATA[Vertical take-off and landing (VTOL) is a type of unmanned aerial vehicle (UAV) that is growing rapidly because its ability to take off and land anywhere in tight spaces. One type of VTOL UAV, the tail-sitter, has the best efficiency. However, besides the efficiency offered, some challenges must still be overcome, including the complexity of combining the ability to hover like a helicopter and fly horizontally like a fixed-wing aircraft. This research has two contributions: in the form of how the analytical model is generated and the tools used (specifically for the small VTOL quad tail-sitter UAV) and how to utilize off-the-shelf components for UAV empirical modeling. This research focuses on increasing the speed and accuracy of the UAV VTOL control design in fixed-wing mode. The first step is to carry out analysis and simulation. The model is analytically obtained using OpenVSP in longitudinal and lateral modes. The next step is to realize this analytical model for both the aircraft and the controls. The third step is to measure the flight characteristics of the aircraft. Based on the data recorded during flights, an empirical model is made using system identification technique. The final step is to vali-date the analytical model with the empirical model. The results show that the characteristics of the analytical mode fulfill the specified requirements and are close to the empirical model. Thus, it can be concluded that the analytical model can be implemented directly, and consequently, the VTOL UAV design and development process has been shortened.]]>
<![CDATA[Optimizing Membership Function Tuning for Fuzzy Control of Robotic Manipulators Using PID-Driven Data Techniques ]]>
<![CDATA[Chotikunnan, Phichitphon]]>;
<![CDATA[Chotikunnan, Rawiphon]]>;
<![CDATA[Nirapai, Anuchit]]>;
<![CDATA[Wongkamhang, Anantasak]]>;
<![CDATA[Imura, Pariwat]]>;
<![CDATA[Sangworasil, Manas]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.18108
<![CDATA[In this study, a method for optimizing membership function tuning for fuzzy control of robotic manipulators using PID-driven data techniques is presented. Traditional approaches for designing membership functions in fuzzy control systems often rely on the experience and knowledge of the system designer, which can lead to suboptimal performance. By utilizing data collected from a PID control system, the proposed method aims to enhance the precision and controllability of robotic manipulators through improved fuzzy logic control. A Mamdani-type fuzzy logic controller was developed and its performance was simulated in Simulink, demonstrating the effectiveness of the proposed optimization technique. The results indicate that the method can outperform conventional P control systems in terms of overshoot reduction while maintaining comparable transient response specifications. This research highlights the potential of the PID-driven data-based approach for optimizing membership function tuning in fuzzy control systems and offers valuable insights for the development and evaluation of fuzzy logic control in robotic manipulators. Future work may focus on further optimization of the tuning process, evaluation of system robustness under various operating conditions, and exploring the integration of other artificial intelligence techniques for improved control performance.]]>
<![CDATA[An Alternative Nonlinear Lyapunov Redesign Velocity Controller for an Electrohydraulic Drive ]]>
<![CDATA[Mintsa, Honorine Angue]]>;
<![CDATA[Eny, Gérémino Ella]]>;
<![CDATA[Senouveau, Nzamba]]>;
<![CDATA[Kenné, Jean-Pierre]]>;
<![CDATA[Nzué, Rolland Michel Assoumou]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17340
<![CDATA[This research aims at developing control law strategies that improve the performances and the robustness of electrohydraulic servosystems (EHSS) operation while considering easy implementation. To address the strongly nonlinear nature of the EHSS, a number of control algorithms based on backstepping approach is intensively used in the literature. The main contribution of this paper is to consider an alternative approach to synthetize a Lyapunov redesign nonlinear EHSS velocity controller. The proposed control law design is based on an appropriate choice of the control lyapunov function (clf), the extension of the Sontag formula and the construction of a nonlinear observer. The clf includes all the three system variable states in a positive define function. The Sontag formula is used in the time derivative of our clf in order to ensure an asymptotic stabilizing controller for regulating and tracking objectives. A nonlinear observer is developed in order to bring to the proposed controller the estimated values of the first and the second time output derivatives. The design, the tuning implementation and the performances of the proposed controller are compared to those of its equivalent backstepping controller. It is shown that the proposed controller is easier to design with simple implementation tuning while the backstepping controller has several complex design steps and implementation tuning issue. Moreover, the best performances especially under disturbance in the viscous damping are achieved with the proposed controller.]]>
<![CDATA[Synthesis of Hybrid Fuzzy Logic Law for Stable Control of Magnetic Levitation System ]]>
<![CDATA[Chiem, Nguyen Xuan]]>;
<![CDATA[Thang, Le Tran]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v4i2.17537
<![CDATA[In this paper, we present a method to design a hybrid fuzzy logic controller (FLC) for a magnetic levitation system (MLS) based on the linear feedforward control method combined with FLC. MLS has many applications in industry, transportation, but the system is strongly nonlinear and unstable at equilibrium. The fast response linear control law ensures that the ball is kept at the desired point, but does not remain stable at that point in the presence of noise or deviation from the desired position. The controller that combines linear feedforward control and FLC is designed to ensure ball stability and increase the system's fast-response when deviating from equilibrium and improve control quality. Simulation results in the presence of noise show that the proposed control law has a fast and stable effect on external noise. The advantages of the proposed controller are shown through the comparison results with conventional PID and FLC control laws.]]>
