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The design of a neural network-based adaptive control method for robotic arm trajectory tracking

  • S.I: AI based Techniques and Applications for Intelligent IoT Systems
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Abstract

With the in-depth development of high-tech industries, especially in the fields of production, manufacturing, aviation, and medical care, most of the work needs to be accomplished with the help of machines. As a high-tech product, a robotic arm plays an irreplaceable role in high-risk and high-precision engineering, such as arc welding, spraying, and assembly. At the same time, with the increasing requirements of scientific and technological production processes, robotic arm tasks are becoming increasingly complicated. Robotic arm trajectory tracking control in industry also has increasingly higher standards. Furthermore, external interference sources invariably affect the robotic arm control system when it is in operation. Therefore, existing manipulator control systems can no longer meet the requirements of industrial production. This paper aims to realize the tracking control of the trajectory of a robotic arm through a neural network algorithm. This research offers an adaptive neural network control method to solve the manipulator trajectory tracking control problem. To increase the control effect and overall performance of the manipulator, a neural network is employed to address the uncertainty in the control system as well as the interference of external elements. Experiments reveal that a neural network-based manipulator trajectory control and tracking system can effectively regulate the manipulator's operation and improve its overall performance.

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Funding

This work was supported by Key Scientific and Technological Project of Henan Province (222102210121).

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Authors and Affiliations

  1. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Kun Xu & Zhiliang Wang

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  1. Kun Xu
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  2. Zhiliang Wang
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Correspondence to Kun Xu.

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Xu, K., Wang, Z. The design of a neural network-based adaptive control method for robotic arm trajectory tracking. Neural Comput & Applic 35, 8785–8795 (2023). https://doi.org/10.1007/s00521-022-07646-y

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  • DOI: https://doi.org/10.1007/s00521-022-07646-y

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