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International Journal of Robotics and Control Systems
Published by Association for Scientific Computing Electronics and Engineering
ISSN : -     EISSN : 27752658     DOI : https://doi.org/10.31763/ijrcs
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
International Journal of Robotics and Control Systems is open access and peer-reviewed international journal that invited academicians (students and lecturers), researchers, scientists, and engineers to exchange and disseminate their work, development, and contribution in the area of robotics and control technology systems experts. Its scope includes Industrial Robots, Humanoid Robot, Flying Robot, Mobile Robot, Proportional-Integral-Derivative (PID) Controller, Feedback Control, Linear Control (Compensator, State Feedback, Servo State Feedback, Observer, etc.), Nonlinear Control (Feedback Linearization, Sliding Mode Controller, Backstepping, etc.), Robust Control, Adaptive Control (Model Reference Adaptive Control, etc.), Geometry Control, Intelligent Control (Fuzzy Logic Controller (FLC), Neural Network Control), Power Electronic Control, Artificial Intelligence, Embedded Systems, Internet of Things (IoT) in Control and Robot, Network Control System, Controller Optimization (Linear Quadratic Regulator (LQR), Coefficient Diagram Method, Metaheuristic Algorithm, etc.), Modelling and Identification System.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 361 Documents
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Dynamic Assessment and Control of a Dual Star Induction Machine State Dedicated to an Electric Vehicle Under Short-Circuit Defect Benbouya, Basma; Cheghib, Hocine; Behim, Meriem; Mahmoud, Mohamed Metwally; Elnaggar, Mohamed F.; Ibrahim, Nagwa F.; Anwer, Noha
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1557

Abstract

The widespread use of electric vehicles (EVs) in several industries gives rise to many significant safety and reliability-related issues. Thus, there is a need for methods for identifying flaws in EV components. In this paper, a state assessment of a dual star induction machine (DSIM) under short-circuit faults is investigated. The DSIM is selected due to its widespread use in high-power applications and its numerous advantages over other conventional machine types. Our focus is particularly on its application in the automotive industry, where its dual stator windings ensure reliable and robust parallel operation, thereby enhancing its robustness and efficiency. To improve this technology and ensure its proper functioning following potential failures and during maintenance, appropriate diagnostic and monitoring methods are essential. Our methodology combines two techniques: the current space vector (CSV), utilized to prevent information loss, and the wavelet packet decomposition energy, calculated from the resulting CSV signals. This approach enables the detection of various stator short-circuit faults, presenting different severities and occurring at different locations. The outcomes of this study, which were verified through the use of a Simulink model of a DSIM devoted to an EV, showcase the efficacy of the suggested approach. Furthermore, this work underscores the significance of this approach in maintaining the performance and reliability of DSIM, particularly in demanding environments such as the automotive industry.
Design, Modeling, and Simulation of A New Adaptive Backstepping Controller for Permanent Magnet Linear Synchronous Motor: A Comparative Analysis Maamar, Yahiaoui; Elzein, I. M.; Alnami, Hashim; Brahim, Brahimi; Benameur, Afif; Mohamed, Horch; Mahmoud, Mohamed Metwally
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1425

Abstract

In this paper, a nonlinear adaptive position controller for a permanent magnet linear synchronous motor based on a newly developed adaptive backstepping control approach is discussed and analyzed. The backstepping approach is a systematic method; it is used for non-linear systems such as the linear synchronous motor. This controller combines the notion of the Lyapunov function, which is based on the definition of a positive energy function; to ensure stability in the sense of Lyapunov, it is necessary to ensure the negativity of this function by a judicious choice of a control variable called virtual control. But this method is mainly based on the mathematical model of the permanent magnet linear synchronous machine (PMLSM) which makes this control sensitive to the variation of the parameters of the machine, to overcome this problem an adaptive control was proposed, the adaptive backstepping control approach is utilized to obtain the robustness for mismatched parameter uncertainties and disturbance load force. The overall stability of the system controller and adaptive low is shown using the Lyapunov theorem. The validity of the proposed controller is supported by computer simulation results.
Development of a Testbed for Autonomous Navigation of an Off-Shelf Quadrotor Based on Ultra-Wide-Band Real-Time Localization Gachoki, Nelson Muchiri; Kamau, Stanley; Ikua, Bernard
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1650

Abstract

Recent advances in autonomous aerial vehicle research, from theoretical simulations to experimental validations, has triggered demand for reliable proof-of-concept test-beds. Although such test-beds have been developed in some advanced drone research laboratories, their cost, expertise and complexity place them out of reach for upcoming research teams. This raises the need for development of less complex and affordable testbeds for quadrotor research. The contribution of this research is provision of low-cost autonomous quadrotor test-bed for proof-of-concept. The development of the proposed testbed entails configuration of Ultra-Wide-Band (UWB) based Real-Time Localization System (RTLS) to transmit position data of multiple agents to LabVIEW software for analysis and decision making. The autonomous navigation commands for the quadrotor are generated from the LabVIEW software and relayed through customized USB interface to the flight control module. The commands alter the digital state of Arduino board pins which are connected to the flight controller hence manipulating navigation pitch and roll parameters. The validation tests performed in the test-bed involved quadrotor hover and navigation in pursuit of the ground agent. The results demonstrate that UWB based RTLS achieves high precision of 99% when the modules are stationary but the precision reduced to 90% when the modules were in motion, which may be attributed actuating signal transmission delays. The results also showed that the Arduino based electronic flight controller is capable of generating flight paths to follow the ground robot in real-time with precision deviations of under 10% which is at par with other research test beds. This novel testbed provides a costeffective and accurate solution for autonomous flight testing, with precision comparable to visual-based testbeds, but at a much lower cost. Further research is encouraged to explore how the system performs with more than two agents and on a wider test arena.
Design of A Backstepping Control and Synergetic Control for An Interconnected Twin-Tanks System: A Comparative Study Al-Majeez, Rawaa; Al-Badri, Kareem; Al-Khazraji, Huthaifa; Ra'afat, Safanah M.
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1682

Abstract

This paper presents a comparative performance examination between designing backstepping control (BSC) and synergetic control (SC) for an interconnected twin-tanks system. The controller is used to maintain the liquid level in the tank at the desired value by manipulating the input flow rate. The nonlinear dynamics of the twin-tanks system is established first. Then, based on the nonlinear dynamics of the system, the control law of the BSC and the SC are developed. The two controllers cooperate with the grasshopper optimization algorithm (GOA) for further improvement of the control design performance by tuning the design parameters of each controller. GOA has strong searchability for optimal solution and it has been successfully used to solve several optimization problems in numerous fields. Finally, the performance and the significance of each controlled system for two case studies (normal operation and under external disturbance) are examined based on MATLAB software. The simulation data shows that the BSC gives better performance than the SC.
Systematic Review of Unmanned Aerial Vehicles Control: Challenges, Solutions, and Meta-Heuristic Optimization Basil, Noorulden; Sabbar, Bayan Mahdi; Marhoon, Hamzah M.; Mohammed, Abdullah Fadhil; Ma'arif, Alfian
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1596

Abstract

Unmanned Aerial Vehicles (UAVs) are powerful tools with vast potential, yet they face significant challenges. One of the primary issues is flight endurance, limited by current battery technology. Researchers are exploring alternative power sources, including hybrid systems and internal combustion engines, and considering docking stations for battery exchange or recharging. Beyond endurance, UAVs must address safety, efficient path planning, payload capacity balancing, and flight autonomy. The complexity increases when considering swarming behaviour, collision avoidance, and communication protocols. Despite these challenges, research continues to unlock UAVs’ potential, with path planning optimization significantly advanced by meta-heuristic algorithms like the Cuckoo Optimization Algorithm (COA). Whereas, meta-heuristic algorithms can be defined as system-level strategies that are used to seek suboptimal solutions to optimization problems. It uses heuristic approaches together with the exploration/exploitation scheme in order to effectively employ within large solution spaces. However, dynamic environments still present difficulties. UAVs have evolved beyond recreational use, becoming essential in industries like agriculture, delivery services, surveillance, and disaster relief. By resolving issues related to autonomy, battery longevity, and security, the benefits of UAV technology can be fully optimized. This systematic review emphasizes the importance of continuous innovation in UAV research to overcome these challenges.
Function Approximation Technique-based Adaptive Force-Tracking Impedance Control for Unknown Environment Azlan, Norsinnira Zainul; Yamaura, Hiroshi; Suwarno, Iswanto
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1029

Abstract

An accurate force-tracking in various applications may not be achieved without a complete knowledge of the environment parameters in the force-tracking impedance control strategy. Adaptive control law is one of the methods that is capable of compensating parameter uncertainties. However, the direct application of this technique is only effective for time-invariant unknown parameters. This paper presents a Function Approximation Technique (FAT)-based adaptive impedance control to overcome uncertainties in the environment stiffness and location with consideration of the approximation error in the FAT representation. The target impedance for the control law have been derived for unknown time-varying environment location and constant or time-varying environment stiffness using Fourier Series. This allows the update law to be derived easily based on Lyapunov stability method. The update law is formulated based on the force error feedback. Simulation results in MATLAB environment have verified the effectiveness of the developed control strategy in exerting the desired amount of force on the environment in x-direction, while precisely follows the required trajectory along y-direction, despite the constant or time-varying uncertainties in the environment stiffness and location. The maximum force error for all unknown environment tested has been found to be less than 0.1 N. The test outcomes for various initial assumption of unknown stiffness between 20000N/m to 120000N/m have shown consistent and excellent force tracking. It is also evident from the simulation results that the proposed controller is effective in tracking time-varying desired force under the limited knowledge of the environment stiffness and location.
Performance Enhancement of Dual-Star Induction Machines Using Neuro-Fuzzy Control and Multi-Level Inverters: A Comparative Study with PI Controllers Mezaache, Salah Eddine; Zaidi, Elyazid
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1670

Abstract

This paper proposes a hybrid speed control strategy for Dual-Star Induction Machines (DSIMs) supplied by Multi-Level Inverters (MLIs). The proposed approach integrates a Neuro-Fuzzy Controller (NFC) with an Indirect Field-Oriented Control (IFOC) technique, leveraging the adaptive learning capabilities of an Artificial Neural Network (ANN) to optimize the NFC parameters. This strategy achieves significant enhancements in speed regulation performance, including a 20% reduction in settling time, a 15% decrease in overshoot, and minimized steady-state error. The NFC's online adaptive learning capability enables real-time adjustments, outperforming the PI controller in handling rotor resistance variations and load disturbances. Simulation results demonstrate a 35% reduction in torque ripple and a 20% improvement in speed regulation compared to PI controllers. The NFC also exhibits faster response times during torque change and remains unaffected by 50% rotor resistance variations. Additionally, the NFC controller achieves up to 51% reduction in Total Harmonic Distortion (THD) compared to the PI controller.  Increasing the inverter voltage level from m=2 to m=7 significantly reduces electromagnetic torque ripple, demonstrating a direct correlation between higher inverter levels and improved torque ripple performance. These improvements position the NFC-based strategy as a promising solution for industrial applications requiring precise speed control, such as robotics, electric vehicles, and automation systems.
Design of a PID Speed Controller for BLDC Motor with Cascaded Boost Converter for High-Efficiency Industrial Applications Al-Dabbagh, Zainab Ameer; Shneen, Salam Waley
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1601

Abstract

Achieving high voltage and efficiency in brushless direct current (BLDC) motor applications is challenging, particularly in industrial settings where precise speed control is essential. This study addresses this issue by designing a cascaded boost converter with a Proportional–integral–derivative (PID) speed controller. The cascaded boost converter is first simulated in an open-loop circuit using MATLAB/SIMULINK, followed by integrating the BLDC motor and adding a PID controller to achieve precise speed control. The PID controller achieved a steady-state speed of 1500 rad/s with an input voltage of 15 volts, resulting in an output voltage of over 50 volts. The efficiency of the system was improved by 87.87% compared to traditional methods. While the PID controller effectively controls the motor speed, it may consume more power and require more complex tuning in certain operating conditions. The proposed system is suitable for high-voltage industrial applications, such as electric vehicle drives and renewable energy systems, where precise speed control and high efficiency are critical.  The PID controller is user-friendly and easy to implement, making it suitable for various industrial applications. The system was tested under varying load conditions and input voltages to ensure robust performance and reliability. Future work will optimize the PID controller for real-time applications and integrate advanced control strategies to enhance system performance. A cascaded boost converter is a type of DC-DC converter that boosts the input voltage to a higher level, while a PID controller is a control loop feedback mechanism widely used for precise control of dynamic systems.
Two-Flexible-Link Manipulator Vibration Reduction Through Fuzzy-Based Position Faris, Waleed F.; Rabie, M.; Moaaz, Ahmad O.; Ghazaly, Nouby M.; Makrahy, Mostafa M.
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1669

Abstract

The increasing demand for robotic applications has emphasized the need for advanced control strategies, particularly for flexible manipulators with lightweight links. These manipulators offer advantages such as reduced energy consumption, increased payload capacity, and precise high-speed operation but face challenges due to oscillations and delays caused by their flexibility. This study evaluates the performance of Fuzzy Logic Control (FLC) and Linear Quadratic Regulator (LQR) techniques for a Quanser two-link flexible manipulator, using quantitative metrics to compare their effectiveness. The LQR controller was implemented using state-space modeling, with weighting matrices Q and R tuned to achieve minimal overshoot and fast settling times. The FLC system employed five triangular membership functions for inputs and outputs, covering normalized ranges of [-1, 1] for angular errors and [-2.75, 2.75] for error rates, with a heuristic rule base designed to optimize performance. Simulations were conducted under step input conditions at target angles of 30° and 60°, with performance evaluated using vibration amplitude, settling time, steady-state error, and overshoot. Quantitatively, the LQR controller reduced vibration amplitudes to 5 radians for a 30° input and achieved settling times of approximately 2 seconds. For the same conditions, the FLC system reduced vibrations further to 4 radians, though with slightly longer settling times of around 2.3 seconds. At a 60° input, LQR vibrations peaked at over 10 radians, while FLC maintained peak vibrations at approximately 4 radians. These results highlight the FLC’s superior vibration suppression, particularly at higher input angles, albeit with marginally slower response times. However, the study was limited to idealized simulation conditions and requires further experimental validation. This research underscores the trade-offs between LQR’s precision and FLC’s adaptability, emphasizing the importance of parameter tuning and system modeling in achieving optimal performance for flexible manipulators.
Detection of Sealing Defects in Canned Sardines Using Local Binary Pattern and Perceptron Techniques for Enhanced Quality Control Mansour, Salah-Eddine; Sakhi, Abdelhak
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1737

Abstract

In the canned sardine production industry, sealing issues often arise due to various factors, such as the quantity of fish in the can or improper calibration of the sealing machine. These sealing defects can result in poorly sealed cans that may explode and contaminate an entire production batch, leading to significant financial losses and damage to the company's reputation. This study proposes an advanced and reliable method for classifying fish can images to detect potential defects, such as sealing issues, which are critical to maintaining quality standards in the canning industry. Our classification method utilizes the Local Binary Patterns (LBP) algorithm for feature extraction across the entire dataset of images. The extracted features are then processed using a Perceptron classifier to identify poorly sealed cans. This approach achieved a precision score of 0.85, demonstrating its effectiveness. Additionally, our analysis revealed that LBP significantly contributes to improving classification accuracy. By automating and enhancing the quality assurance process, this method provides the canning industry with a robust tool for ensuring high product standards, minimizing errors, and increasing efficiency in production lines.

Page 27 of 37 | Total Record : 361

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