Process control system and method with improved distribution, installation and validation of components
    6.
    发明授权
    Process control system and method with improved distribution, installation and validation of components 有权
    具有改进组件分布,安装和验证的过程控制系统和方法

    公开(公告)号:US06501995B1

    公开(公告)日:2002-12-31

    申请号:US09345215

    申请日:1999-06-30

    IPC分类号: G05B1500

    摘要: A control system has blocks or other components that facilitate validation of their own replacements, e.g., downloaded via e-commerce transactions. The system includes first and second process control components. The first component is coupled to a third process control component, with which it transfers information, e.g., as part of an active or ongoing control process. The second component can be, for example, an update or other potential replacement for the first component. The first and/or second components can effect substitution of the second component for the first. More particularly, they can effect coupling of the second component for information transfer with the third component and decoupling of the first component from such transfer with the third component. Preferably, such coupling and decoupling occur while the process control system remains active.

    摘要翻译: 控制系统具有促进自己的替换的验证的块或其它组件,例如通过电子商务交易下载。 该系统包括第一和第二过程控制组件。 第一组件耦合到第三过程控制组件,其通过该组件传送信息,例如作为主动或正在进行的控制过程的一部分。 第二组件可以是例如第一组件的更新或其他潜在替换。 第一和/或第二组分可以实现第二组分对第一组分的替代。 更具体地,它们可以实现用于信息传送的第二组件与第三组件的耦合,并且使第一组件与第三组件的转移脱钩。 优选地,当过程控制系统保持活动时,发生这种耦合和解耦。

    Method and apparatus for controlling multivariable nonlinear processes
    7.
    发明授权
    Method and apparatus for controlling multivariable nonlinear processes 失效
    用于控制多变量非线性过程的方法和装置

    公开(公告)号:US5566065A

    公开(公告)日:1996-10-15

    申请号:US333539

    申请日:1994-11-01

    IPC分类号: G05B13/02

    摘要: A method and apparatus for a robust process control system which utilizes a neural-network based multivariable inner-loop PD controller cascaded with decoupled outer-loop controllers with integral action, the combination providing a multivariable nonlinear PID and feedforward controller. The inner-loop PD controller employs a quasi-Newton iterative feedback loop structure whereby the manipulated variables are computed in an iterative fashion as a function of the difference between the inner loop setpoint and the predicted controlled variable as advanced by the optimum prediction time, in order to incorporate the downstream limiting effects on the non-limited control loops. The outer-loop controllers compensate for unmodeled process changes, unmeasured disturbances, and modeling errors by adjusting the inner-loop target values.

    摘要翻译: 一种用于鲁棒过程控制系统的方法和装置,其利用基于神经网络的多变量内环路控制器与具有积分作用的解耦外环控制器级联,该组合提供多变量非线性PID和前馈控制器。 内环PD控制器采用准牛顿迭代反馈回路结构,其中操作变量以迭代方式计算,作为内部循环设定点与预测控制变量之间的差值的函数,如最佳预测时间所推进, 以将下游限制效应纳入非限制性控制回路。 外环控制器通过调整内环目标值来补偿未建模的过程变化,未测量的干扰和建模误差。

    Multivariable nonlinear process controller
    8.
    发明授权
    Multivariable nonlinear process controller 失效
    多变量非线性过程控制器

    公开(公告)号:US5570282A

    公开(公告)日:1996-10-29

    申请号:US333161

    申请日:1994-11-01

    IPC分类号: G05B13/02 G06F15/18

    摘要: A method and apparatus for a robust process control system that utilizes a neural-network multivariable inner-loop PD controller cascaded with decoupled outer-loop controllers with integral action, the combination providing a multivariable nonlinear PID and feedforward controller. The inner-loop neural-network controller is trained to achieve optimal performance behavior when future process behavior repeats the training experience. The outer-loop controllers compensate for process changes, unmeasured disturbances, and modeling errors. In the first and second embodiments, the neural network is used as an inner-loop controller in a process control system having a constraint management scheme which prevents integral windup by controlling the action of the outer-loop controllers when limiting is detected in the associated manipulated-variable control path. In the second and third embodiments, the neural-network controller is used without the integral controllers or the constraint management scheme as a simple PD feedforward controller.

    摘要翻译: 一种用于鲁棒过程控制系统的方法和装置,其利用与具有积分作用的解耦外环控制器级联的神经网络多变量内环PD控制器,该组合提供多变量非线性PID和前馈控制器。 当未来的过程行为重复训练经验时,训练内环神经网络控制器以实现最佳性能行为。 外环控制器补偿过程变化,未测量的干扰和建模误差。 在第一和第二实施例中,神经网络用作具有约束管理方案的过程控制系统中的内环控制器,该约束管理方案通过在相关联的被操纵的控制系统中检测到限制时控制外环控制器的动作来防止积分 变量控制路径。 在第二和第三实施例中,神经网络控制器在没有集成控制器或约束管理方案的情况下被用作简单的PD前馈控制器。

    Methods and apparatus for object-based process control
    9.
    发明授权
    Methods and apparatus for object-based process control 有权
    基于对象的过程控制的方法和设备

    公开(公告)号:US06510352B1

    公开(公告)日:2003-01-21

    申请号:US09627466

    申请日:2000-07-28

    IPC分类号: G05B1101

    摘要: The provides improved control devices, systems and methods for operation thereof. These rely on control devices that provide virtual machine environments in which Java objects, or other such software constructs, are executed to implement control (e.g., to monitor and/or control a device, process or system). These objects define blocks which are the basic functional unit of the control. They also define the input, output and body parts from which blocks are formed, and the signals that are communicated between blocks. The objects also define nested and composite groupings of blocks used to control loops and higher-level control functions.

    摘要翻译: 提供改进的控制装置,其操作的系统和方法。 这些依赖于提供虚拟机环境的控制设备,其中Java对象或其他此类软件构造被执行以实现控制(例如,监视和/或控制设备,过程或系统)。 这些对象定义作为控件的基本功能单元的块。 它们还定义了形成块的输入,输出和主体部分以及在块之间传递的信号。 这些对象还定义了用于控制循环和更高级别控制功能的块的嵌套和复合分组。

    Method and apparatus for providing multivariable nonlinear control
    10.
    发明授权
    Method and apparatus for providing multivariable nonlinear control 失效
    提供多变量非线性控制的方法和装置

    公开(公告)号:US5704011A

    公开(公告)日:1997-12-30

    申请号:US333095

    申请日:1994-11-01

    IPC分类号: G05B13/02 G05B13/04 G05B13/00

    摘要: A method and apparatus for training and optimizing a neural network for use in controlling multivariable nonlinear processes. The neural network can be used as a controller generating manipulated variables for directly controlling the process or as part of a controller structure generating predicted process outputs. The neural network is trained and optimized off-line with historical values of the process inputs, outputs, and their rates of change. The determination of the manipulated variables or the predicted process outputs are based on an optimum prediction time which represents the effective response time of the process output to the setpoint such that the greatest change to the process output occurs as a result of a small change made to its paired manipulated variable.

    摘要翻译: 一种用于训练和优化用于控制多变量非线性过程的神经网络的方法和装置。 神经网络可以用作产生用于直接控制过程的操纵变量的控制器,或作为生成预测过程输出的控制器结构的一部分。 神经网络与过程投入,产出及其变化率的历史价值离线进行培训和优化。 操纵变量或预测过程输出的确定基于最佳预测时间,其表示过程输出到设定点的有效响应时间,使得对过程输出的最大变化是由于对 其配对操纵变量。