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Distributed formation control of nonholonomic autonomous vehicle via RBF neural network

机译：基于RBF神经网络的非完整自主车辆的分布式编队控制。

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摘要

In this paper, RBF neural network consensus-based distributed control scheme is proposed for nonholonomic autonomous vehicles in a pre-defined formation along the specified reference trajectory. A variable transformation is first designed to convert the formation control problem into a state consensus problem. Then, the complete dynamics of the vehicles including inertia, Coriolis, friction model and unmodeled bounded disturbances are considered, which lead to the formation unstable when the distributed kinematic controllers are proposed based on the kinematics. RBF neural network torque controllers are derived to compensate for them. Some sufficient conditions are derived to accomplish the asymptotically stability of the systems based on algebraic graph theory, matrix theory, and Lyapunov theory. Finally, simulation examples illustrate the effectiveness of the proposed controllers.
机译：本文提出了一种基于RBF神经网络基于共识的分布式控制方案，该方案针对非完整自动驾驶车沿指定的参考轨迹以预定义的形式进行。首先设计变量转换，以将地层控制问题转换为状态共识问题。然后，考虑了包括惯性，科里奥利，摩擦模型和未建模的有界扰动在内的车辆的完整动力学，当基于运动学提出分布式运动学控制器时，会导致地层不稳定。导出了RBF神经网络扭矩控制器以对其进行补偿。基于代数图论，矩阵论和李雅普诺夫论，得出了一些足够的条件来实现系统的渐近稳定性。最后，仿真示例说明了所提出控制器的有效性。

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  • 来源
    《Mechanical systems and signal processing》 |2017年第ptab期|81-95|共15页
  • 作者

    Shichun Yang; Yaoguang Cao; Zhaoxia Peng; Guoguang Wen; Konghui Guo;

  • 作者单位

    School of Transportation Science and Engineering, Beihang University, Beijing, 100191, PR China,Beijing Engineering Center for Clean Energy & High Efficient Power, Beihang University, Beijing 100191, PR China;

    School of Transportation Science and Engineering, Beihang University, Beijing, 100191, PR China;

    School of Transportation Science and Engineering, Beihang University, Beijing, 100191, PR China,Beijing Engineering Center for Clean Energy & High Efficient Power, Beihang University, Beijing 100191, PR China;

    Department of Mathematics, Beijing Jiaotong University, Beijing 100044, PR China;

    College of Automotive Engineering, Jilin University, Jilin 130012, PR China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Vehicle; Formation control; RBF neural network; Graph theory; Filippov solution;

    机译：车辆;编队控制;RBF神经网络;图论;Filippov解决方案;

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