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    • 1. 发明授权
    • Method and apparatus for controlling the operating characteristic
quantities of an internal combustion engine
    • 用于控制内燃机的工作特性量的方法和装置
    • US4827937A
    • 1989-05-09
    • US831476
    • 1986-02-20
    • Rolf KohlerPeter J. SchmidtManfred Schmitt
    • Rolf KohlerPeter J. SchmidtManfred Schmitt
    • F02D45/00F02B1/04F02C9/00F02C9/28F02D41/14F02D41/24
    • F02D41/2454F02B1/04F02D41/2477
    • The invention relates to a method and apparatus for controlling operating characteristic quantities of an internal combustion engine. For issuing an uncorrected anticipatory control value, a characteristic field is addressed by directing pregiven operating characteristic quantities as addresses and, with a simultaneously superposed control, an averaged value of the control factor is applied to the anticipatory control region for effecting an adaptive learning procedure. From the averaged control factor, a global factor is defined which works multiplicatively on the entire basic characteristic field. This considers especially multiplicative disturbance influences. Also, by means of a dividing of the self-adaptive characteristic field into a non-changeable basic characteristic field and into at least one further changeable factor characteristic field corresponding thereto, each basic value is multiplied within a pregiven influence region by means of the associated factor of the factor characteristic field whereby mostly additive disturbing influences are considered. Global factor and the particular factor from the factor characteristic field can conjointly work upon the control value issued by the basic characteristic field.
    • 本发明涉及一种用于控制内燃机的工作特性量的方法和装置。 为了发出未校正的预期控制值,通过将预先设定的工作特征量指定为地址来寻址特征字段,并且通过同时叠加的控制将控制因子的平均值应用于预期控制区域以实现自适应学习过程。 根据平均控制因子,定义了一个在整个基本特征领域中乘法运算的全局因子。 这特别考虑到乘法扰动的影响。 此外,通过将自适应特征场划分成不可改变的基本特征场,并将其与至少一个与之对应的其它可变因子特征场分开,通过相关联的每个基本值在预先设定的影响区域内相乘 考虑因素特征场因子,主要是加性扰动影响。 全局因子和因子特征领域的特殊因素可以结合基本特征领域发布的控制值。
    • 2. 发明授权
    • Method and apparatus for controlling the operating characteristic
quantities of an internal combustion engine
    • 用于控制内燃机的工作特性量的方法和装置
    • US4901240A
    • 1990-02-13
    • US6696
    • 1987-01-21
    • Peter J. SchmidtManfred Schmitt
    • Peter J. SchmidtManfred Schmitt
    • F02D45/00F02D41/14F02D41/24
    • F02D41/2454
    • In a method and an apparatus for open-loop and closed-loop control of operating characteristic quantities of an internal combustion engine, it is proposed that the anticipatory or pilot control area, which is variable by means of learning, be embodied such that in a factor characteristic field associated with a basic characteristic field, not only the particular support point but with decreasing influence outward the area surrounding it as well are changed by the carry-over of an averaged regulating factor value. Alternatively, or preferably combined therewith, the factor characteristic field is replaced by at least two correcting characteristic fields, which have larger inclusion areas, overlapping one another, for each support point, so that even in the event of fluctuations of input quantities about a border of an area, at least one of the correcting characteristic fields will be addressed.
    • 在用于内燃机的工作特征量的开环和闭环控制的方法和装置中,提出通过学习可变的预期或先导控制区域被体现为在 与基本特征场相关联的因子特征场,不仅特定的支持点,而且随着其周围的区域的减小也受到平均调节因子值的转移而改变。 替代地,或优选地与其组合,因子特征字段被至少两个修正特征字段替换,所述校正特征字段对于每个支持点具有较大的包含区域,彼此重叠,使得即使在关于边界的输入量的波动的情况下 的区域中,校正特征字段中的至少一个将被解决。
    • 9. 发明授权
    • Method for training a neural network
    • 训练神经网络的方法
    • US06968327B1
    • 2005-11-22
    • US10049650
    • 2000-08-24
    • Ronald KatesNadia HarbeckManfred Schmitt
    • Ronald KatesNadia HarbeckManfred Schmitt
    • A61B5/00G06F19/00G06N3/08G06E1/00G06E3/00G06F15/18G06G7/00
    • G06N3/08A61B5/00A61B5/415A61B5/418A61B5/7267G06F19/00
    • A method for training a neural network in order to optimize the structure of the neural network includes identifying and eliminating synapses that have no significant influence on the curve of the risk function. First and second sending neurons are selected that are connected to the same receiving neuron by respective first and second synapses. It is assumed that there is a correlation of response signals from the first and second sending neurons to the same receiving neuron. The first synapse is interrupted and a weight of the second synapse is adapted in its place. The output signals of the changed neural network are compared with the output signals of the unchanged neural network. If the comparison result does not exceed a predetermined level, the first synapse is eliminated, thereby simplifying the structure of the neural network.
    • 用于训练神经网络以优化神经网络的结构的方法包括识别和消除对风险函数的曲线没有显着影响的突触。 选择通过相应的第一和第二突触连接到相同接收神经元的第一和第二发送神经元。 假设存在来自第一和第二发送神经元到相同接收神经元的响应信号的相关性。 第一突触中断,第二突触的重量适应其位置。 将改变的神经网络的输出信号与不变神经网络的输出信号进行比较。 如果比较结果不超过预定水平,则消除第一突触,从而简化了神经网络的结构。
    • 10. 发明授权
    • Valve arrangement
    • 阀门布置
    • US5499657A
    • 1996-03-19
    • US410792
    • 1995-03-27
    • Manfred Schmitt
    • Manfred Schmitt
    • F16K27/00D01D1/06F16K1/22F16K11/052F16K11/20F16K11/22
    • F16K1/222Y10T137/87877Y10T137/87909
    • A valve arrangement including a distributor housing (2) with a distributor duct (4), an inlet duct (46) which leads into the distributor duct (4), at least two outlet ducts (11, 12, 13) which lead out of the distributor duct (4), and a value associated with eac;h outlet duct. The values are integrated into the distributor housing (2) and have regulating flaps (31, 32, 33) whose axes of rotation (37, 38, 39) are arranged such that the flaps are situated partially in the distributor duct (4) and partially in the associated outlet duct (11, 12, 13). This construction reduces the overall size of the valve arrangement and eliminates dead spaces in which medium flowing through the valve arrangement could become trapped.
    • 一种阀装置,包括具有分配器管道(4)的分配器壳体(2),引入分配器管道(4)的入口管道(46),至少两个引出管道的输出管道(11,12,13) 分配器管道(4),以及与eac; h出口管道相关联的值。 这些值被集成到分配器壳体(2)中并且具有其旋转轴线(37,38,39)被布置成使得翼片部分地位于分配器管道(4)中的调节翼片(31,32,33),并且 部分地在相关的出口管道(11,12,13)中。 这种结构减小了阀门装置的总体尺寸,并且消除了流过阀装置的介质可能被困住的空隙。