案例3：储罐液位控制-MV Horizon（范围）和POV Impulse Factor（脉冲因子）

带回家的消息
SMOCPro中存在两种方法模拟基础层串联修正。一方面用户可以通过利用GMB中的“PID”模块明确地模拟流程基础层的组成。在这种情况下，模型包括了过程输出测量变量（PV）和控制器输出（OP），其中OP是回路内部的。在这种情况下需要对模型指定正确的PID参数。另一方面，串级校正也可通过选择含闭环动态模型块内的“PID/Cascade Loop”标签进行建模。该标签将自动生成包含正确模型预测的额外模块。这两种方法都可能会放弃合适的控制，但是，勾选的“PID/Casdcade Loop”标签选项必须确保所考虑的闭环是稳定的。如果使用明确的PID模块，用户必须小心确认闭环是稳定的。

---

Take Home Message
There exist two ways in SMOCPro to model base layer cascade correction. On the one hand the user can explicitly model the base layer component of the process by utilizing the “PID” block in the GMB. In this case the model includes the measurement of the process output variable (PV) AND the controller output (OP), where the OP is internal to the loop. In this case the correct PID parameters need to be specified for the model. On the other hand, cascade correction may also be modeled by selecting the “PID/Cascade Loop” flag inside the model block containing the closed loop dynamics. This flag automatically generates extra blocks required to incorporate the correct model predictions. Both methodologies may yield appropriate control, however, the option of checking the “PID/Casdcade Loop” flag ensures that the closed loop under consideration is stable. If utilizing the explicit PID block the user must take care in ensuring that the closed loop is stable.

---

---

案例3：储罐液位控制-MV Horizon（范围）和POV Impulse Factor（脉冲因子）
(\ProgramFiles\ShellGlobalSolutions\PCTP\Tutorial\SMOCPro\Tutorial3_TankLevel_MV Horizon.wsp)
(\ProgramFiles\ShellGlobalSolutions\PCTP\Tutorial\SMOCPro\Tutorial3_TankLevel_Impulse Factor.wsp)
(\ProgramFiles\ShellGlobalSolutions\PCTP\Tutorial\SMOCPro\Tutorial3_TankLevel_DisturbanceRejection.wsp)
本案例所考虑的应用是一个容器内的单输入单输出（SISO）液位控制问题。该案例改编自一个实施于水处理单元的大型控制器。本教程旨在说明SMOCPro控制积分CVs中使用的两个重要概念：
 操作变量（MV）horizon（范围），和
 POV Impulse Factor（脉冲因子）。
MV Horizon（范围）研究
下图包含了所考虑的SISO容器工艺示意图。

Figure 7. Tank process flow scheme.
图7：储罐工艺流程图
过程模型
SMOCPro控制器模型包含了1个操作变量（出口流体阀位OP），1个过程输出变量（容器液位）和1个干扰变量（进口流量），并且编译设定周期为1.0min。下图显示了用于合成控制器的GMB模型。

Figure 8. Tank graphical model.
图8：储罐模型图表
模型块的颜色编码突出了感兴趣的不同变量，并且与仿真曲线有相同的颜色：干扰变量是紫色，被控变量是红色，操作变量是蓝色。
从模型中我们可以看出，液位干扰存在着两个可能的来源：进口流量（DV）和Ramp_1不可测量干扰变量(UNM)。进出罐变量的不平衡将导致液位的升高或降低。
编译模型后，树状列表的Model Analysis（模型分析）节点显示了静态“增益”矩阵。在这里青色格子表示实际上“增益”是一个坡值（斜坡）（-0.1 1/dT dT=1min）。

---

原文：
Case 3: Tank Level Control—MV Horizon and POV Impulse Factor
The application under consideration in this example is a single-input single-output (SISO) Level control problem in a vessel. The case study was extracted and adapted from a large controller implemented on a water treatment unit. This tutorial aims to illustrate two important concepts utilized in SMOCPro for controlling ramp CVs:
 Manipulated variable (MV) horizon, and
 POV Impulse Factor.
**MV Horizon Study **
The figure below contains the process schematic under consideration for the SISO vessel.
Process Model
The SMOCPro controller model contains one manipulated variable (outlet flow valve position OP), one process output variable (vessel level) and one measured disturbance (inlet flow) and is compiled with a period of 1.0 minute. The figure below shows the GMB model used for the synthesis of the controller.
The color coding in the model blocks highlights the different variables of interest and will be the same color of the simulation curves: disturbance variable in purple, controlled variable in red and manipulated variable in blue.
From the model, we can see that there are two possible sources for Level disturbances: the Inlet Flow (DV) and the Ramp_1 unmeasured disturbance variable (UNM). Any imbalance between the variables coming into and out of the vessel results in an increase or decrease in the Level.
After compiling the model, the Model Analysis node in the tree displays the static “gain” matrix. Here, the cyan color of the cell means that the “gain” is in fact a slope (ramp) value of –0.1 1/dT (with dT = 1 min.).

---

2016.5.18