An integrated drive assembly control method, system, and integrated drive assembly

By combining a joint state observer and a radial basis function neural network, the problem of low control accuracy of rope tension and arm shape in a rope-driven super-redundant robotic arm was solved, achieving high-precision rope drive force control and stable operation.

CN122299646APending Publication Date: 2026-06-30CHONGQING UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHONGQING UNIV
Filing Date
2026-04-15
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing rope-driven super-redundant robotic arms have low precision in controlling rope tension and arm shape, making it difficult to achieve high-precision control. Furthermore, rope length is easily affected by temperature and load, and lacks effective management and compensation.

Method used

The system employs a joint state observer combined with a radial basis function neural network to calculate rope tension and joint state by acquiring operational data. It then performs precise control based on rope constraints and achieves high-precision drive through a servo motor, reducer, and lead screw-nut mechanism. A floating compensation mechanism is also provided to maintain rope pretension.

Benefits of technology

It achieves precise and coordinated control of the rope drive force, improves the control accuracy of the robotic arm and its adaptability to environmental changes, avoids interference and wear between ropes, and ensures the long-term stable operation of the drive assembly.

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Abstract

This application provides an integrated drive assembly control method, system, and integrated drive assembly, relating to the field of power control technology. The method includes: acquiring operating state data of the integrated drive assembly; calculating the tension of a rope using the operating state data; inputting the tension into a pre-constructed joint state observer; obtaining the joint state of a robotic arm through the joint state observer; wherein the joint state observer is constructed based on a dynamic model and a radial basis function neural network; outputting joint adjustment parameters based on the joint state and operating state data; and inputting the joint adjustment parameters into a controller of the integrated drive assembly, the controller being used to control the integrated drive assembly based on the joint adjustment parameters to adjust the driving force of the rope. This application solves the problems of compact integration of multiple drive units, precise transmission, and dynamic compensation of rope tension in the prior art.
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