Research on intelligent control of automobile active suspension based on BP neural control model

Yulong Zhou; Kaizhong Si; Jinlong Xia; Zhiqiang Xie; Fanglong Li

doi:10.1117/12.3025576

28 February 2024 Research on intelligent control of automobile active suspension based on BP neural control model

Yulong Zhou, Kaizhong Si, Jinlong Xia, Zhiqiang Xie, Fanglong Li

Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 1307129 (2024) https://doi.org/10.1117/12.3025576
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China

Abstract

This study aims to study intelligent control of automotive active suspension based on the BP neuronal control model. By analyzing the deficiency of the traditional active suspension system, the BP neuronal control model is introduced to improve the control accuracy and robustness of the system. In this study, the BP neuronal control model is used to simulate the dynamic behavior of an automotive active suspension system by building a neural network. By adjusting the parameters and structure of the neural network, the performance of the active suspension system is optimized. Experimental results show that intelligent control of active vehicle suspension based on BP neuronal control model can effectively improve vehicle driving stability and comfort. Compared to the traditional active suspension system, the new model offers significant advantages in terms of control accuracy and robustness. In addition, the experimental data also show that the neural control model can adjust the parameters of the suspension system in real time, to adapt to different road conditions and vehicle load changes. This research provides a new solution for intelligent control of automotive active suspension. Intelligent control of automotive active suspension based on BP neuronal control model has high control accuracy and robustness, and can adapt to different road conditions and vehicle load changes. Future research can further optimize the neural control model and improve its performance in practical applications.

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

Citation Download Citation

Yulong Zhou, Kaizhong Si, Jinlong Xia, Zhiqiang Xie, and Fanglong Li "Research on intelligent control of automobile active suspension based on BP neural control model", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 1307129 (28 February 2024); https://doi.org/10.1117/12.3025576

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KEYWORDS

Data modeling

Neural networks

Education and training

Control systems

Artificial neural networks

Performance modeling

Roads

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