Abstract
With the continuous advancement of electric vehicles and smart internet technologies, ensuring vehicle safety through electromagnetic compatibility (EMC) testing in complex electromagnetic environments has become increasingly critical. However, due to the significant variability in vehicle response characteristics under electromagnetic interference, traditional PID control methods for steering robots struggle to meet the high-precision requirements of such tests. In this study, a novel fuzzy PID parameter self-tuning method is proposed, leveraging a Sparrow Search Algorithm-Back Propagation (SSA-BP) neural network. This method optimizes the fuzzy controller's quantization factor by constructing a neural network system where the expected motor angle serves as the input and the quantization factor as the output. The quantization factor is then calibrated online through iterative training.The proposed approach enables the steering robot to achieve real-time, adaptive tuning of the PID parameters for the drive motor by adjusting the steering torque according to different vehicle characteristics, thereby enhancing the robot's anti-interference capability and robustness in EMC testing. The effectiveness of this method is validated through Matlab/Simulink simulations, experiments conducted on the Sensodrive platform, and tests performed in an EMC anechoic chamber. The results indicate that the method offers substantial improvements in control accuracy and anti-interference capabilities, highlighting its strong potential for practical application.
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Funding
This work was supported by [the National Key Research and Development Program of China] (Grant numbers [No. 2022YFB4701104]), [Natural Science Foundation of Hebei Province of China] (Grant numbers [No. F2021202062]) and [National Natural Science Foundation of China] (Grant numbers [No. U1913211]).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [Xuan Liu], [Yuzhe Xing],[Yuqing Liu] and [Yuan Wan]. The first draft of the manuscript was written by [Yuzhe Xing] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Xuan Liu made substantial contributions to the conception or design of the work. Yuzhe Xing drafted the work or revised it critically for important intellectual content. Yuqing Liu analyzed and processed data. Yuan Wan agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
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Project supported by the National Key Research and Development Program of China (No. 2022YFB4701104),Natural Science Foundation of Hebei Province of China (No. F2021202062), National Natural Science Foundation of China (No. U1913211).
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Liu, X., Xing, Y., Liu, Y. et al. Study on Self-tuning of Robot Parameters for EMC Vehicle Steering Test. J Intell Robot Syst 110, 170 (2024). https://doi.org/10.1007/s10846-024-02200-5
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DOI: https://doi.org/10.1007/s10846-024-02200-5