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1. 发明申请

US20060293817A1 Intelligent electronically-controlled suspension system based on soft computing optimizer 审中-公开
标题翻译：基于软计算优化器的智能电子控制悬架系统
公开(公告)号：US20060293817A1
公开(公告)日：2006-12-28
申请号：US11159830
申请日：2005-06-23
申请人： Takahide Hagiwara , Sergei Panfilov , Sergei Ulyanov
发明人： Takahide Hagiwara , Sergei Panfilov , Sergei Ulyanov
IPC分类号： B60G17/018 , G06F17/00
CPC分类号： B60G17/018 , B60G17/0152 , B60G2500/10 , B60G2600/187 , B60G2600/1879
摘要： A Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a suspension system is described. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and/or output variables; the type of fuzzy inference model (e.g., Mamdani, Sugeno, Tsukamoto, etc.); and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a response of the actual suspension system model of the controlled suspension system. The SC optimizer produces a robust KB that is typically smaller that the KB produced by prior art methods.
摘要翻译：描述了用于设计用于控制悬架系统的控制系统中的知识库（KB）的软计算（SC）优化器。 SC优化器包括基于模糊神经网络（FNN）的模糊推理机。 SC优化器提供模糊推理系统（FIS）结构选择，FIS结构优化方法选择和教学信号选择与生成。用户选择模糊模型，包括以下一个或多个：输入和/或输出变量的数量; 模糊推理模型的类型（例如，Mamdani，Sugeno，Tsukamoto等）; 和初步类型的会员职能。遗传算法（GA）用于优化语言变量参数和输入 - 输出训练模式。 GA也用于优化规则库，使用模糊模型，最优语言变量参数和教学信号。 GA产生近乎最佳的FNN。可以使用经典的基于导数的优化程序来改进近似最优的FNN。 GA发现的FIS结构通过基于受控悬架系统的实际悬架系统模型的响应的适应度函数进行了优化。 SC优化器产生通常比现有技术方法产生的KB更小的鲁棒KB。

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