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METHOD, UNIT, AND SYSTEM FOR INTELLIGENT CONTROL BASED UPON SOFT CALCULATION

机译:基于软件计算的智能控制方法,单元和系统

摘要

PROBLEM TO BE SOLVED: To decrease the number of sensors in use without a significant loss of control precision by constituting a 2nd control system by using a 1st and a 2nd control signal. ;SOLUTION: A sensor corrector 460 is used as a 1st adaptation function for (2nd genetic algorithm: GA2 444) and calculates information reference as the maximum of mutual information between two control signals xa and ya. An entropy model 442 gives physical reference as minimum entropy generation (used as 2nd adaptation function of GA2 444) by using the information from a sensor 482. The output of the GA2 444 is a tutor signal 447 for a fuzzy neural network(FNN) 2 486 and used on-line to generate the deletion control signal ya, so that the quality of a deletion control signal yb is similar to that of the optimum control signal xa. Then an optimizing device 440 provides the correction of the control signal ya for off-line inspection from the FNN 2 486 by using new information reference.;COPYRIGHT: (C)2000,JPO
机译:要解决的问题:通过使用第一和第二控制信号构成第二控制系统,减少使用的传感器数量而不会显着降低控制精度。解决方案:传感器校正器460用作(第二遗传算法:GA2 444)的第一自适应函数,并且计算信息参考作为两个控制信号xa和ya之间的互信息的最大值。熵模型442通过使用来自传感器482的信息,给出物理参考作为最小熵产生(用作GA2 444的第二自适应函数)。GA2444的输出是用于模糊神经网络(FNN)2的导师信号447。删除控制信号yb的质量类似于图486中所示的信号,并且在线用于生成删除控制信号ya,从而删除控制信号yb的质量类似于最佳控制信号xa的质量。然后,优化设备440通过使用新的信息参考,对控制信号ya进行校正,以从FNN 2486进行离线检查; COPYRIGHT:(C)2000,JPO

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