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    • 1. 发明授权
    • Optimization control method for shock absorber
    • 减震器优化控制方法
    • US06496761B1
    • 2002-12-17
    • US09724581
    • 2000-11-28
    • Sergei V. UlyanovTakahide Hagiwara
    • Sergei V. UlyanovTakahide Hagiwara
    • B60G2300
    • G05B13/0285B60G17/018B60G17/0182B60G2200/142B60G2202/135B60G2206/99B60G2400/821B60G2500/10B60G2600/1878B60G2600/1879G05B13/0265G05B13/027
    • A control system for optimizing the performance of a vehicle suspension system by controlling the damping factor of one or more shock absorbers is described. The control system uses a fitness (performance) function that is based on the physical laws of minimum entropy. The control system uses a fuzzy neural network that is trained by a genetic analyzer. The genetic analyzer uses a fitness function that maximizes information while minimizing entropy production. The fitness function uses a difference between the time differential of entropy from a control signal produced in a learning control module and the time differential of the entropy calculated by a model of the suspension system that uses the control signal as an input The entropy calculation is based on a dynamic model of an equation of motion for the suspension system such that the suspension system is treated as an open dynamic system.
    • 描述了通过控制一个或多个减震器的阻尼系数来优化车辆悬架系统的性能的控制系统。 控制系统使用基于最小熵的物理定律的适应度(性能)函数。 控制系统使用由遗传分析仪训练的模糊神经网络。 遗传分析仪使用最大化信息的适应度函数,同时最小化熵产生。 适应度函数使用来自学习控制模块中产生的控制信号的熵的时间差与通过使用控制信号作为输入的悬架系统的模型计算的熵的时间微分之差。熵计算基于 在悬架系统的运动方程的动态模型上,使得悬架系统被视为开放动态系统。