Integration of Adaptive PID and Fuzzy Logic Controller for Improved Precision and Stability in Robotic Arms

This paper introduces the integration of adaptive PID and fuzzy logic controllers to improve precision and stability in robotic arms. The proposed approach optimizes the strengths of both control techniques to improve overall system performance. PID controllers offer robust control and stability, particularly for linear and time-invariant systems, while fuzzy logic controllers provide adaptive control in the presence of nonlinear systems and uncertainties. Combining both controllers improves system response, characterized by minimized overshoot, reduced steady-state errors, and faster settling times. Comparative analysis of simulation and experimental results demonstrates that the combined PID and fuzzy logic controller outperforms individual controllers in transient and steady-state performance, indicating its suitability for advanced robotic arm applications.

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Publication Details

Published
2025-08-27
DOI
https://doi.org/10.1109/inecce64959.2025.11150931
Primary Topic
Robot Manipulation and Learning
Type
article
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article

Integration of Adaptive PID and Fuzzy Logic Controller for Improved Precision and Stability in Robotic Arms

Muhammad Luqman Muhd Zain, Wan Faizura Wan Tarmizi, Fahmi Samsuri
Robot Manipulation and Learning
article

Integration of Adaptive PID and Fuzzy Logic Controller for Improved Precision and Stability in Robotic Arms

Muhammad Luqman Muhd Zain, Wan Faizura Wan Tarmizi, Fahmi Samsuri
article en

Abstract

This paper introduces the integration of adaptive PID and fuzzy logic controllers to improve precision and stability in robotic arms. The proposed approach optimizes the strengths of both control techniques to improve overall system performance. PID controllers offer robust control and stability, particularly for linear and time-invariant systems, while fuzzy logic controllers provide adaptive control in the presence of nonlinear systems and uncertainties. Combining both controllers improves system response, characterized by minimized overshoot, reduced steady-state errors, and faster settling times. Comparative analysis of simulation and experimental results demonstrates that the combined PID and fuzzy logic controller outperforms individual controllers in transient and steady-state performance, indicating its suitability for advanced robotic arm applications.

Universiti Malaysia Pahang Al-Sultan Abdullah (MY), TATI University College (MY)
Openalex Percentile: Top 70%
Robot Manipulation and Learning
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