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All Journal Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems
Prinyakupt, Jaroonrut
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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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.
Co-Authors Angsuwatanakul, Thanate Chotikunnan, Phichitphon Chotikunnan, Rawiphon Imura, Pariwat Khotakham, Wanida Pititheeraphab, Yutthana Puttasakul, Tasawan Srisiriwat, Anuchart Thongpance, Nuntachai