基于模糊神经网络的智能履带车路径跟踪系统

    Path following system based on fuzzy neural networks for intelligently tracked vehicle

    • 摘要: 履带车适合于松软地面作业,其在结构化环境中能够自动驾驶功能具有重要的意义。介绍了基于模糊神经网络的智能履带车路径跟踪系统。该系统是模糊控制和神经网络控制的有机结合体,除了保留常规模糊控制器的自然语言信息处理功能以外,同时具有神经控制系统的监督学习及知识获取功能,这使得控制系统对变化的工作环境具有更好的适应性。试验表明:该控制系统对变化路径的跟踪响应迅速、反应敏感,能够满足路径实时跟踪的要求,效果较好。

       

      Abstract: The intelligently tracked vehicle is fit for working on soft ground, and its auto drive function is of great significance. This paper introduces the path following system of an intelligently tracked vehicle using fuzzy neural networks. The system, which is an integral combination of the fuzzy system and artificial neural system, can not only deal with information expressed linguistically, but also possess the same function of supervised learning and knowledge acquisition as the artificial neural networks. Therefore, the system is more adaptable to its working environment. The test shows that the system follows the changing path at a rapid speed, and can efficiently satisfy the demands of real time path following.

       

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