DEVELOPMENT OF MATHEMATICAL SUPPORT FOR ADAPTIVE CONTROL FOR THE INTELLIGENT GRIPPER OF THE COLLABORATIVE ROBOT MANIPULATOR
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Abstract
The relevance of this study is due to the growing demands for intelligent robotic systems capable of safe interaction with humans in a collaborative work environment. It is especially important to provide adaptive control of grippers, which allows manipulators to accurately and delicately grasp objects of various shapes, masses, and stiffness. The subject of the research is the process of controlling a gripper as part of a collaborative robot manipulator, and the topic is the development of effective mathematical software for adapting control parameters in real time. The aim of the work is to improve the accuracy, reliability, and flexibility of the intelligent gripper by integrating Sensor Fusion and Neuro-PID control methods. In the course of the study, methods of mathematical modeling, sensor information processing, and numerical error analysis based on experimental data were used. The developed model takes into account the symmetry of the applied forces and ensures stable control of the gripping force, as evidenced by the results of experiments on controlling the asymmetric error and the control signal. The analysis showed that the deviations of the gripping error remain within ±0.2 N, and the control signal has smoothed dynamics without sharp impulses, which provides an adaptive response to external changes. The conclusions confirm the feasibility of the proposed approach to improve the control efficiency of robotic grippers. The scope of the results includes industrial collaborative robots, automated warehousing systems, manipulation of delicate objects, and biomedical robotic systems where high accuracy and adaptability of interaction is required.
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