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All Journal Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems Journal of Fuzzy Systems and Control (JFSC) Control Systems and Optimization Letters
Chotikunnan, Phichitphon
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Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Mechanical Engineering

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Hybrid Fuzzy-Expert System Control for Robotic Manipulator Applications Chotikunnan, Phichitphon; Roongprasert, Kittipan; Chotikunnan, Rawiphon; Pititheeraphab, Yutthana; Puttasakul, Tasawan; Wongkamhang, Anantasak; Thongpance, Nuntachai
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.24956

Abstract

This research examines a hybrid fuzzy-expert system for the control of robotic manipulators, integrating the flexibility of fuzzy logic with the analytical decision-making capabilities of expert systems. The hybrid system switches dynamically between triangle membership functions, which facilitate smooth transitions, and trapezoidal membership functions, which efficiently manage sudden step changes. This adaptive technique mitigates the shortcomings of independent fuzzy logic controllers, particularly their inconsistency across varied setpoints. Simulation outcomes demonstrate substantial decreases in overshoot and settling time, as well as enhanced adaptability and flexibility in dynamic settings. A comparison test shows that the hybrid system is better than separate triangular and trapezoidal fuzzy controllers because it chooses the best control strategy based on the setpoint attributes in real time. Although there are occasional compromises in accuracy (IAE and RMSE), the hybrid controller provides balanced performance appropriate for various robotic applications. The results confirm its viability as a dependable option for industrial and medical robots, particularly in applications necessitating precision control and adaptability.
Comparative Analysis of Fuzzy Membership Functions for Step and Smooth Input Tracking in a 3-Axis Robotic Manipulator Chotikunnan, Phichitphon; Chotikunnan, Rawiphon; Pititheeraphab, Yutthana; Puttasakul, Tasawan; Wongkamhang, Anantasak; Thongpance, Nuntachai
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.278

Abstract

Robotic manipulators are essential in industrial and medical applications, requiring precise control to improve efficiency and reduce errors. This research looks at how well fuzzy logic controllers using Gaussian, generalized bell, triangular, and trapezoidal membership functions can handle step and smooth inputs for a robot system that is meant to move materials. Critical metrics like steady-state values, overshoot, rise time, integral absolute error (IAE), and root mean square error (RMSE) were tested using five different methods. The results showed that both the Gaussian and extended bell functions found a good balance between being stable and being responsive. This made them useful for situations with moderate to high input levels. While triangular functions displayed enhanced responsiveness, they also revealed heightened overshoot. In contrast, trapezoidal functions demonstrated significant stability at high saturation levels, although they had challenges in attaining smooth transitions. These findings highlight the necessity of choosing membership functions according to particular application needs. This study investigates the utilization of hybrid methodologies and adaptive optimization strategies to improve fuzzy control systems. These concepts offer compelling approaches to improve accuracy and resilience in dynamic robotic settings.
Comparative Analysis of PID Tuning Methods for Speed Control in Mecanum-Wheel Electric Wheelchairs Thongpance, Nuntachai; Chotikunnan, Phichitphon; Wongkamhang, Anantasak; Chotikunnan, Rawiphon; Imura, Pariwat; Khotakham, Wanida; Nirapai, Anuchit; Roongprasert, Kittipan
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13046

Abstract

This study compares two PID controller tuning methods, particle swarm optimization (PSO) and Cohen-Coon, employed for speed control of an omnidirectional Mecanum-wheel electric wheelchair. Mecanum wheels improve maneuverability on powered mobility platforms; yet, controlling these systems is difficult due to nonlinearities and directional coupling effects. This work investigates the effectiveness of PSO as a sophisticated alternative to traditional PID tuning methods, effectively tackling this issue. This study evaluates P, PI, PD, and PID controllers tuned by both Cohen-Coon and PSO methods, applied to a DC motor system simulating real-world wheelchair actuation. Step response-based system identification models the motor using MATLAB/Simulink. Simulations of a 12V DC motor are examined using controlled-step time-domain inputs. Every controller configuration is subjected to evaluation for overshoot, root mean square error (RMSE), rise time, and settling time. The PSO-tuned PID controller exhibited enhanced performance, characterized by a rise time of 2.06 s, a settling time of 2.37 s, an overshoot of 0.78%, and an RMSE of 4.59, far surpassing the Cohen-Coon variant, which had a settling time of 6.12 s and an overshoot of 20.14%. The results indicate that PSO enhances both transient and steady-state performance in intricate and disturbance-sensitive systems, including Mecanum wheelchairs. Despite PSO's increased computing complexity during offline tuning and the necessity for meticulous parameter selection, its advantages can be precomputed and effectively utilized in real-time embedded systems. This study highlights the importance of safety, dependability, and responsiveness, illustrating that PSO is a scalable and efficient method for improving assistive robotic systems.
Enhancing MG996R Servo Motor Performance Using PSO-Tuned PID and Feedforward Control Chotikunnan, Phichitphon; Pititheeraphab, Yutthana; Angsuwatanakul, Thanate; Prinyakupt, Jaroonrut; Puttasakul, Tasawan; Chotikunnan, Rawiphon; Thongpance, Nuntachai
International Journal of Robotics and Control Systems Vol 5, No 2 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i2.1854

Abstract

The aim of this research is to improve the precision of factory-locked MG996R servo motors, which are frequently employed in biomedical and robotic applications. These motors are characterized by the absence of inherent feedback channels and adjustable internal settings. The proposed technique proposes a non-invasive control strategy that utilizes externally obtained feedback to enable closed-loop control without requiring any modifications to the interior circuitry. The scientific contribution consists of the development of an outer-loop PID control framework that has been optimized using Particle Swarm Optimization (PSO) and enhanced with feedforward compensation. By utilizing the inherent potentiometer, this method ensures the preservation of hardware integrity and enables real-time angle feedback. A model fit of 96.94% was achieved by establishing a second-order discrete-time model using MATLAB's System Identification Toolbox. Particle Swarm Optimization (PSO) was employed to optimize PID improvements offline by minimizing the Integral of Squared Error (ISE). In both experimental and simulated environments, the controller's effectiveness was assessed using 2 rad/s sine wave inputs and a 10° step. The PSO-PID with feedforward controller achieved optimal results, achieving an RMSE of 0.5313° and an MAE of 0.1630° in simulations, as well as an MAE of 0.8497° in hardware step response. The requirement for gain scaling in embedded systems was underscored by the instability of the standalone PSO-PID controller. This method offers a pragmatic, scalable solution for applications such as assistive robotics, prosthetic joints, and surgical instruments. In order to achieve sub-degree precision in safety-critical environments, future endeavors will entail the implementation of adaptive gain tuning and enhanced resolution sensing.
Noise-Reduced 3D Organ Modeling from CT Images Using Median Filtering for Anatomical Preservation in Medical 3D Printing Chotikunnan, Phichitphon; Chotikunnan, Rawiphon; Puttasakul, Tasawan; Khotakham, Wanida; Imura, Pariwat; Prinyakupt, Jaroonrut; Thongpance, Nuntachai; Srisiriwat, Anuchart
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.26665

Abstract

This study offers a systematic approach to improving the reconstruction of three-dimensional anatomical models from CT imaging data. The main difficulty tackled is the maintenance of internal bone features during denoising, essential for producing clinically relevant models. A nonlinear filtering strategy was implemented, utilizing a 3×3 median filter alongside manual refinement to eliminate salt-and-pepper noise while preserving anatomical information. The study presents a reproducible image-processing pipeline that improves structural clarity and enables material-efficient 3D printing while preserving internal bone integrity. A publicly available dataset including 813 anonymized chest CT scans (512×512 pixels, 16-bit grayscale) from Zenodo was employed. Preprocessing included grayscale normalization, brightness adjustment, and the application of median filters with kernel sizes from 3×3 to 9×9, followed by artifact removal using FlashPrint software before STL conversion. The 3×3 median filter achieved an excellent balance between noise reduction and anatomical clarity, outperforming mean filtering and larger kernels in maintaining edge detail. Although statistical evaluation was not conducted, visual analysis validated an 18.07 percent decrease in print time and a 17.88 percent reduction in filament consumption. The technology exhibited actual efficacy in generating high-quality anatomical models. Future endeavors will incorporate automated segmentation and sophisticated denoising methodologies to enhance applicability in surgical simulation, clinical education, and personalized healthcare planning.
Comparative Analysis of PID-Driven Data-Based and PSO-Tuned Fuzzy Membership Functions for Robotic Manipulator Control Chotikunnan, Phichitphon; Khotakham, Wanida; Imura, Pariwat; Chotikunnan, Rawiphon; Wongkamhang, Anantasak; Thongpance, Nuntachai
Journal of Fuzzy Systems and Control Vol. 3 No. 3 (2025): Vol. 3 No. 3 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i3.335

Abstract

Robotic manipulators require control systems that are both responsive and precise in order to ensure accurate tracking and stability in dynamic environments. Conventional fuzzy logic controllers that are based on proportional integral derivative (PID) methods frequently encounter difficulties in achieving fast response, minimal steady-state error, and low overshoot. This study presents a comparative evaluation of a PID-driven data-based fuzzy logic controller and a particle swarm optimization (PSO) tuned fuzzy logic controller for a three-axis robotic manipulator implemented in Simulink. Both controllers used Gaussian membership functions within a Mamdani inference structure. The PSO algorithm was employed to optimize fuzzy input-scaling gains using a composite performance index that incorporated absolute error, control effort, overshoot penalty, and steady-state error. The simulation results indicate that the PSO-tuned controller consistently outperformed the benchmark. On the R-axis, it shortened rise and settling times and reduced overshoot, mean absolute error (MAE), and root mean square error (RMSE). On the T-axis, response speed and error values improved, although overshoot increased, indicating a trade-off between speed and stability. On the Z-axis, the PSO controller achieved a substantial decrease in overshoot, lower error metrics, and faster stabilization. Overall, the PSO-based tuning process preserved steady-state stability while improving transient performance on all axes. These findings show that metaheuristic optimization is an effective and practical method for enhancing fuzzy logic controllers in robotic manipulators. This approach has potential applications in precision manufacturing, service automation, and surgical robotics.
Optimizing Light Intensity with PID Control Alfian, Eriko; Ma'arif, Alfian; Chotikunnan, Phichitphon; Abougarair, Ahmed Jaber
Control Systems and Optimization Letters Vol 1, No 3 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i3.38

Abstract

Lighting is a fundamental cornerstone within interior design, possessing the capability to metamorphose spaces and evoke emotional responses profoundly. This principle applies to residential, industrial, and office domains, where lighting nuances are meticulously adjusted to enhance comfort and practicality. However, adequate luminance frequently intersects with energy wastage, often attributed to negligent light management practices. Mitigating this issue necessitates integrating light intensity controls adept at adapting to ambient luminosity and room-specific parameters. A prospective avenue encompasses incorporating a Proportional Integral Derivative (PID) control system synergized with light sensors. This research Implementing a closed-loop architecture, PID control utilizes feedback mechanisms to improve the precision of instrumentation systems. The PID methodology, consisting of Proportional, Integral, and Derivative control modalities, produces stable responses, accelerates system reactions, and diminishes deviations and overshooting by predetermined setpoints. The proposed Light Intensity Control System underpinned by PID methodology manifests as an exhibition of compelling outcomes drawn from empirical trials. The judicious selection of optimal parameters, specifically Kp = 0.2, Ki = 0.1, and Kd = 0.1, yielded noteworthy test outcomes: an ascent time of 0.0848, an overshoot of 6.5900, a culmination period of 0.4800, a settling period of 2.3032, and a steady-state error of 0.0300. Within this system, the PID controller assumes a pivotal role, orchestrating the regulation and meticulous calibration of light intensity to harmonize with designated criteria, thus fostering an environment of augmented energy efficiency and adaptability in illumination.Lighting is a fundamental cornerstone within interior design, possessing the capability to metamorphose spaces and evoke emotional responses profoundly. This principle applies to residential, industrial, and office domains, where lighting nuances are meticulously adjusted to enhance comfort and practicality. However, adequate luminance frequently intersects with energy wastage, often attributed to negligent light management practices. Mitigating this issue necessitates integrating light intensity controls adept at adapting to ambient luminosity and room-specific parameters. A prospective avenue encompasses incorporating a Proportional Integral Derivative (PID) control system synergized with light sensors. This research Implementing a closed-loop architecture, PID control utilizes feedback mechanisms to improve the precision of instrumentation systems. The PID methodology, consisting of Proportional, Integral, and Derivative control modalities, produces stable responses, accelerates system reactions, and diminishes deviations and overshooting by predetermined setpoints. The proposed Light Intensity Control System underpinned by PID methodology manifests as an exhibition of compelling outcomes drawn from empirical trials. The judicious selection of optimal parameters, specifically Kp = 0.2, Ki = 0.1, and Kd = 0.1, yielded noteworthy test outcomes: an ascent time of 0.0848, an overshoot of 6.5900, a culmination period of 0.4800, a settling period of 2.3032, and a steady-state error of 0.0300. Within this system, the PID controller assumes a pivotal role, orchestrating the regulation and meticulous calibration of light intensity to harmonize with designated criteria, thus fostering an environment of augmented energy efficiency and adaptability in illumination.
Co-Authors Abougarair, Ahmed Jaber Alfian Ma’arif Alfian, Eriko Angsuwatanakul, Thanate Chotikunnan, Rawiphon Imura, Pariwat Javana, Kanyanat Keawkao, Supachai Khotakham, Wanida Minyong, Panya Nirapai, Anuchit Panomruttanarug, Benjamas Pisa, Pawichaya Pititheeraphab, Yutthana Prinyakupt, Jaroonrut Puttasakul, Tasawan Roongpraser, Kittipan Roongprasert, Kittipan Sangworasil, Manas Srisiriwat, Anuchart Thajai, Phanassanun Thongpance, Nuntachai Wongkamhang, Anantasak Wuttipan, Nathamon