ADAPTIVE CONTROL STRATEGIES FOR PRECISION ENHANCEMENT IN ROBOTIC MANIPULATOR SYSTEMS

Abstract

Adaptive control strategies have become a significant advancement in modern robotic manipulator systems, particularly in environments requiring high precision, adaptability, and real-time response. This study focuses on the role of adaptive control techniques in enhancing the performance of robotic manipulators by improving accuracy, stability, and reducing system errors under dynamic working conditions.The research examines key variables such as Adaptive Gain Tuning, Sensor Feedback Accuracy, System Responsiveness, and Computational Delay, and their impact on Precision Enhancement in robotic systems. The study is based on a structured quantitative approach using data collected from 108 respondents including robotics engineers, automation professionals, and researchers. The Structural Equation Modeling (SEM) technique using AMOS software is applied to analyze relationships between variables and validate the proposed conceptual framework. The results indicate that Adaptive Gain Tuning and Sensor Feedback Accuracy have a strong positive influence on precision enhancement, while Computational Delay negatively affects system performance. System Responsiveness plays a supporting role in improving trajectory tracking and operational stability. The model demonstrates good statistical fit and explains a significant level of variance in robotic precision. The study concludes that adaptive control strategies are essential for improving robotic manipulator performance and are highly relevant for industrial automation, intelligent manufacturing, and advanced robotic applications.