Base long short-term memory network and proportional integral derivative control on machine arm

Jinhuang Chen; Yifeng Liu; Zhaoqi Chen; Jianwen Liang; Peiqi Tu; Jinzong Zhang

doi:10.1117/12.3034812

11 July 2024 Base long short-term memory network and proportional integral derivative control on machine arm

Jinhuang Chen, Yifeng Liu, Zhaoqi Chen, Jianwen Liang, Peiqi Tu, Jinzong Zhang

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 1321016 (2024) https://doi.org/10.1117/12.3034812
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

To achieve high-precision control at a lower cost, researchers propose combining the traditional machine arm method with new hardware, Long-short Term Memory (LSTM) Network, and Proportional Integral Derivative (PID) Control. The machine arm method provides reliable control but lacks precision. LSTM Networks capture long-term dependencies, improving accuracy. PID Control continuously adjusts control signals for stability. This integrated approach offers a cost-effective solution for industries seeking precise control.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinhuang Chen, Yifeng Liu, Zhaoqi Chen, Jianwen Liang, Peiqi Tu, and Jinzong Zhang "Base long short-term memory network and proportional integral derivative control on machine arm", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 1321016 (11 July 2024); https://doi.org/10.1117/12.3034812

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