Advances in nano research

  • 제13권6호
  • /
  • Pages.587-597
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  • 2022
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  • 2287-237X(pISSN)
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  • 2287-2388(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Multi-system vehicle formation control based on nearest neighbor trajectory optimization

  • Mingxia, Huang (School of Transportation and Geomaitics Engineering, Shenyang Jianzhu University) ;
  • Yangyong, Liu (College of Intelligent Manufacturing and Automotive, Chongqing Vocational College of Transportation) ;
  • Ning, Gao (School of Transportation and Geomaitics Engineering, Shenyang Jianzhu University) ;
  • Tao, Yang (China railway Shenyang Bureau Group Co., Ltd)
  • 투고 : 2022.01.07
  • 심사 : 2022.05.17
  • 발행 : 2022.12.25
⟨ 이전 논문 다음 논문 ⟩

초록

In the present study, a novel optimization method in formation control of multi -system vehicles based on the trajectory of the nearest neighbor trajectory is presented. In this regard, the state equations of each vehicle and multisystem is derived and the optimization scheme based on minimizing the differences between actual positions and desired positions of the vehicles are conducted. This formation control is a position-based decentralized model. The trajectory of the nearest neighbor are optimized based on the current position and state of the vehicle. This approach aids the whole multi-agent system to be optimized on their trajectory. Furthermore, to overcome the cumulative errors and maintain stability in the network a semi-centralized scheme is designed for the purpose of checking vehicle position to its predefined trajectory. The model is implemented in Matlab software and the results for different initial state and different trajectory definition are presented. In addition, to avoid collision avoidance and maintain the distances between vehicles agents at a predefined desired distances. In this regard, a neural fuzzy network is defined to be utilized in conjunction with the control system to avoid collision between vehicles. The outcome reveals that the model has acceptable stability and accuracy.

키워드

참고문헌

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