公开(公告)号：EP0712060B1

公开(公告)日：2000-08-02

申请号：EP95307798.9

申请日：1995-11-01

Applicant: THE FOXBORO COMPANY

Inventor： Hansen, Peter D. ,  Badavas, Paul C.

IPC: G05B13/02

CPC classification number: G05B13/027 ,  G05B13/026 ,  Y10S706/903 ,  Y10S706/906

公开(公告)号：EP0712060A1

公开(公告)日：1996-05-15

申请号：EP95307798.9

申请日：1995-11-01

Applicant: THE FOXBORO COMPANY

Inventor： Hansen, Peter D. ,  Badavas, Paul C.

IPC: G05B13/02

CPC classification number: G05B13/027 ,  G05B13/026 ,  Y10S706/903 ,  Y10S706/906

Abstract: 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.

Abstract translation: 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。 操作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。

公开(公告)号：EP1126348A3

公开(公告)日：2004-12-22

申请号：EP01102846.1

申请日：2001-02-13

Applicant: The Foxboro Company

Inventor： Goskel, Bulent ,  Hansen, Peter D.

IPC: G05D7/06

CPC classification number: G05D7/005

Abstract: A feed-forward flow controller (155) is designed to calculate a target valve position from a target flow. Correction is made for liquid or gas pressure drop across the valve (105, 115) and for the valve flow modulating member geometry. This feed-forward action may also be used to linearize a feed-back flow control loop.

公开(公告)号：EP0710902B1

公开(公告)日：1999-09-08

申请号：EP95307800.3

申请日：1995-11-01

Applicant: THE FOXBORO COMPANY

Inventor： Hansen, Peter D. ,  Badavas, Paul C.

IPC: G05B13/02

CPC classification number: G05B13/027 ,  G05B13/026 ,  Y10S706/906

公开(公告)号：EP0710902A1

公开(公告)日：1996-05-08

申请号：EP95307800.3

申请日：1995-11-01

Applicant: THE FOXBORO COMPANY

Inventor： Hansen, Peter D. ,  Badavas, Paul C.

IPC: G05B13/02

CPC classification number: G05B13/027 ,  G05B13/026 ,  Y10S706/906

Abstract: 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.

Abstract translation: 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PD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。 内循环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，如预测最佳预测时间， 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。

公开(公告)号：EP1126348A2

公开(公告)日：2001-08-22

申请号：EP01102846.1

申请日：2001-02-13

Applicant: The Foxboro Company

Inventor： Goskel, Bulent ,  Hansen, Peter D.

IPC: G05D7/06

CPC classification number: G05D7/005

Abstract: A feed-forward flow controller (155) is designed to calculate a target valve position from a target flow. Correction is made for liquid or gas pressure drop across the valve (105, 115) and for the valve flow modulating member geometry. This feed-forward action may also be used to linearize a feed-back flow control loop.

Abstract translation: 前馈流量控制器（155）被设计成从目标流量计算目标阀位置。 对阀（105,115）和阀流量调节构件几何形状的液体或气体压降进行校正。 这种前馈动作也可以用于线性化反馈流量控制回路。

公开(公告)号：EP0710901B1

公开(公告)日：2000-09-27

申请号：EP95307799.7

申请日：1995-11-01

Applicant: THE FOXBORO COMPANY

Inventor： Hansen, Peter D. ,  Badavas, Paul C.

IPC: G05B13/02

CPC classification number: G05B13/026 ,  C08F2400/02 ,  G05B13/027

公开(公告)号：EP0710901A1

公开(公告)日：1996-05-08

申请号：EP95307799.7

申请日：1995-11-01

Applicant: THE FOXBORO COMPANY

Inventor： Hansen, Peter D. ,  Badavas, Paul C.

IPC: G05B13/02

CPC classification number: G05B13/026 ,  C08F2400/02 ,  G05B13/027

Abstract: 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.

Abstract translation: 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路PD控制器，该组合提供多变量非线性PID和前馈控制器。 训练内环神经网络控制器以在未来的过程行为重复训练经验时实现最佳性能行为。 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，所述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。