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    • 8. 发明授权
    • Planning method and system
    • 规划方法和制度
    • US5623580A
    • 1997-04-22
    • US274016
    • 1994-07-12
    • Haruki InoueHiroyuki IchikawaHideo YoshidaYasuhiro TeradaNoboru AbeYoshiyuki SatohMasakazu YahiroAkemi Ohtsuki
    • Haruki InoueHiroyuki IchikawaHideo YoshidaYasuhiro TeradaNoboru AbeYoshiyuki SatohMasakazu YahiroAkemi Ohtsuki
    • G06F9/44B65G61/00G06F19/00G06N5/04G06Q10/00G06Q10/04G06Q10/06G06Q50/00G06Q90/00G06F15/18
    • G06Q10/06
    • A planning system for quickly forming the optimum plan for a given planning problem, includes a setting unit for accepting the given planning problem; an optimization unit for creating an objective function which expresses an item intended to be minimized or maximized in the planning problem, and for executing a process which minimizes or maximizes a value of the created objective function; a storage unit for storing therein, at least, constant values which are required for the optimizing process; and a display unit for displaying a processed result of the optimization unit. The optimization unit performs a first function of calculating a difference value between the values of the objective function assumed in a last formed plan and a newly formed plan, and performs a second function of comparing the difference value of the objective function with the constant value set in the storage unit, and then substituting the last formed plan by the newly formed plan and setting the latter as a candidate for an optimum plan, on condition that the difference value of the objective function is smaller than the constant value.
    • 一个规划系统能够快速形成一个给定的规划问题的最优方案,其中包括一个用于接受给定规划问题的设置单元; 用于创建表达在计划问题中被最小化或最大化的项目的目标函数的优化单元,以及用于执行最小化或最大化所创建的目标函数的值的过程; 存储单元,用于至少存储优化处理所需的常数值; 以及显示单元,用于显示优化单元的处理结果。 优化单元执行计算最终形成的计划中假设的目标函数的值与新形成的计划之间的差值的第一函数,并且执行将目标函数的差值与常数值集合进行比较的第二函数 在存储单元中,然后通过新形成的计划代替最后形成的计划,并将后者设置为最佳计划的候选,条件是目标函数的差值小于常数值。
    • 9. 发明授权
    • Method and system for process control with complex inference mechanism
using qualitative and quantitative reasoning
    • 使用定性和定量推理的复杂推理机制的过程控制方法和系统
    • US5377308A
    • 1994-12-27
    • US013953
    • 1993-02-05
    • Haruki InoueMotohisa FunabashiMasakazu YahiroYoshiyuki Satoh
    • Haruki InoueMotohisa FunabashiMasakazu YahiroYoshiyuki Satoh
    • G05B13/02G06N5/04G06N7/04G06F15/00G06F9/44
    • G06N7/04G05B13/0295G06N5/048Y10S706/90Y10S706/906Y10S706/908Y10S706/91
    • A process control system for controlling a process exhibiting both linear behavior and non-linear behavior with a plurality of control quantities has a knowledge base storing therein universal facts, production rules including expert's empirical rules, meta rules describing flows of inferences, algorithm methods by mathematical expressions and membership functions referenced in fuzzy inference and a complex inference mechanism. The complex inference mechanism is composed of a complex fuzzy mechanism for inferring directly predicted values on a multi-dimensional space generated by a plurality of elements for evaluation and predicted control objectives evaluated previously with fuzzy quantities, a predicting fuzzy mechanism having the input supplied with the predicted values for determining arithmetically correlation to the membership functions determined previously with the fuzzy quantities and a satisfaction grade obtained by imparting weight to the correlation for each of the control objectives to thereby determine such a combination of the control quantities for control effectors to vary the operation states thereof from the current operation states that the satisfaction grade becomes maximum, and a main inference mechanism having the input supplied with process data to thereby compare selectively the process data with the knowledge stored in the knowledge base for thereby making decision of the process behavior through a forward fuzzy inference with the aid of the production rules based on the empirical knowledge and manage the whole process control system including the complex fuzzy inference mechanism, the predicting fuzzy inference mechanism and the knowledge base. The system can be advantageously employed for intra-tunnel ventilation control and other processes exhibiting both linear and non-linear behaviors.
    • 用于控制具有多个控制量的线性行为和非线性行为的过程的过程控制系统具有在其中存储通用事实的知识库,包括专家经验规则的生产规则,描述推理流的元规则,通过数学的算法方法 模糊推理中引用的表达式和隶属函数以及复杂的推理机制。 复杂推理机制由复杂的模糊机制组成,用于推断由多个元素产生的多维空间上的直接预测值,用于评估以前用模糊量估计的预测控制目标,预测模糊机制具有提供的输入 用于确定与先前用模糊量确定的隶属函数的算术相关性的预测值,以及通过对每个控制目标赋予相关性而获得的满足度等级,从而确定控制效果器的控制量的组合以改变操作 来自当前操作的状态表明满意等级变为最大,并且具有输入的主推理机制提供过程数据,从而选择性地比较过程数据与知识库中存储的知识,从而进行处理行为的决定 借鉴基于实证知识的生产规则,通过前向模糊推理,对包括复杂模糊推理机制,预测模糊推理机制和知识库的整个过程控制系统进行管理。 该系统可以有利地用于隧道内通气控制和呈现线性和非线性行为的其它过程。
    • 10. 发明授权
    • Method and system for process control with complex inference mechanism
using qualitative and quantitative reasoning
    • 使用定性和定量推理的复杂推理机制的过程控制方法和系统
    • US5251285A
    • 1993-10-05
    • US712104
    • 1991-06-07
    • Haruki InoueMotohisa FunabashiMasakazu YahiroYoshiyuki Satoh
    • Haruki InoueMotohisa FunabashiMasakazu YahiroYoshiyuki Satoh
    • G05B13/02G06N5/04G06N7/04G06F15/00
    • G06N7/04G05B13/0295G06N5/048Y10S706/90Y10S706/906Y10S706/908Y10S706/91
    • A prediction control of a process containing a non-linear behavior is effected by predicting a transition of process quantities (control quantities) of an object to be controlled a predetermined time period after the current time to provide predicted values and by determining manipulation quantities of at least a control effector in accordance with a difference between the predicted values and predetermined target values of the controlled object. A quantitative operation is carried out arithmetically identifying a process as a linear behavior, and a fuzzy inference or qualitative operation, including a fuzzy rule based on empirical knowledge, is carried out for simulating a process, wherein for input process information and current manipulation quantities to be maintained, both operations parallelly determine predicted values of control quantities. A process behavior determination is arithmetically carried out to determine whether the process linearly behaves (i.e. the normal state or the state dominant to statistic distribution) or not (i.e. the extreme transition state such as a transient response, or an indeterminate state) from the specified process information on the basis of a process behavior determination rule. As a result, a predicted value acquired by the quantitative operation is selected in response to a determination of a linear behavior, and a predicted value acquired by the fuzzy inference operation is selected in response to a determination of a non-linear behavior.
    • 包含非线性行为的处理的预测控制通过预测在当前时间之后的预定时间段内要控制的对象的处理量(控制量)的转变来提供预测值,并且通过确定在 根据控制对象的预测值和预定目标值之间的差异,至少控制效应器。 进行定量操作,将过程作为线性行为进行算术识别,进行模糊推理或定性操作,包括基于经验知识的模糊规则,用于模拟过程,其中对于输入过程信息和当前操作量 维持两个操作并行确定控制量的预测值。 算术过程执行过程行为确定,以确定过程是否从指定的过程线性表现(即,统计分布的正常状态或统计分布的统计状态)(即极端过渡状态,如瞬态响应或不确定状态) 基于过程行为确定规则处理信息。 结果,响应于线性行为的确定来选择通过定量操作获取的预测值,并且响应于非线性行为的确定来选择通过模糊推理操作获取的预测值。