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Dergiler / Sakarya University Journal of Science / 2026 / Volume: 30 Issue: 5

Adaptive Inertia Related Control for High Precision Tracking and Stability in Low-Cost Robot Arms

Dilaver Karadaban(IZMIR KATIP CELEBI UNIVERSITY)0009-0001-9059-5567
Kamil Çetin(IZMIR KATIP CELEBI UNIVERSITY)0000-0003-1029-5626
Sayfa
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Yayın Tarihi
2026-10-30
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

This quantitative analysis validates the enhanced robustness of the AIRC, highlighting its potential as a cost-effective and high-performance robotic control system for industrial and research applications.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This study presents the implementation and performance evaluation of an Adaptive Inertia-Related Controller (AIRC) designed for the joint-space control of a low-cost robotic manipulator.
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Temel Bulgular & Veri:The control strategy is implemented within a model-based adaptive framework, with Lyapunov stability analysis ensuring the asymptotic convergence of tracking errors.
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Sonuç & Katkı:This quantitative analysis validates the enhanced robustness of the AIRC, highlighting its potential as a cost-effective and high-performance robotic control system for industrial and research applications.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Robot arm · Adaptive control · PD control

Abstract

This study presents the implementation and performance evaluation of an Adaptive Inertia-Related Controller (AIRC) designed for the joint-space control of a low-cost robotic manipulator. Addressing the limitations of traditional Proportional-Derivative (PD) controllers, particularly operating in dynamic uncertainty conditions and with low sensor-motor accuracy, the applied AIRC adaptively estimates real-time dynamic model parameters to achieve robust and precise trajectory tracking. The control strategy is implemented within a model-based adaptive framework, with Lyapunov stability analysis ensuring the asymptotic convergence of tracking errors. Advanced simulations and real-time experiments were conducted under the same conditions to evaluate the performance of AIRC compared to a standard PD controller. The experimental results confirm a significant improvement in tracking accuracy; specifically, the AIRC reduced the RMSE by approximately 13.6% and 12.9% for Joints 1 and 2, respectively, while achieving a 36.6% improvement for Joint 3 compared to the PD controller. This quantitative analysis validates the enhanced robustness of the AIRC, highlighting its potential as a cost-effective and high-performance robotic control system for industrial and research applications.

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Bu Makaleye Atıf Yap

Karadaban, D., Çetin, K. (2026). Adaptive Inertia Related Control for High Precision Tracking and Stability in Low-Cost Robot Arms. Sakarya University Journal of Science, Volume: 30 Issue: 5. https://doi.org/10.16984/saufenbilder.1818587

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