A3. Overview of Building Blocks-3

塔板负荷（CTL）：
该模块用于计算精馏塔的负荷条件。计算值可用于APC防止塔液泛的参考信息或控制条件。
约束推杆：
该算法是一种在线闭环单变量优化技术。
压力补偿温度（PCT）：
塔板上液体的组成通常与该层板上的温度和压力相关。在APC中，该模块常用于精馏塔控制，如切点控制。
附加模块：
控制应用的时间监控，用于抑制控制信号噪声的先进信号滤波器。
在横河电机DCS中，COAST模块运行在FCS下。有关详细信息，用户可参考COAST模块手册和项目文档。

Exarqe：鲁棒质量预估器：

该软件包适用于抗干扰且高持续精度的预估测量。该软件包有时也被称为“软测量传感器”，用于提供化学品分析/质量的相关信息。
预估量是基于选中的简单测量值（温度，压力，流量...）预测关键产品质量或复杂过程变量当前值的计算变量（CV）（由于显著的延迟或可靠性差等原因其不能在线测量，但测量要求不频繁时可用）。在典型应用中，RQE为闭环控制提供了过程计算值。如图3.0a所示，RQE特别适用于Exasmoc APC策略的应用。
Exarqe有一个离线设计工具，用于创建Exarqe在线文件，它在Exasmoc站上运行。详情请参考Exarqe手册和项目文件。

A3.1构建Exasmoc控制器的基本流程图

下文介绍的基本流程图将使用户了解为APC项目创建Exasmoc在线控制器的基本步骤。 此外，它还为不习惯使用SMOC离线设计和仿真包的用户提供SMOC-PC（脱机开发工具）感知。详细信息可在相应的手册中找到。

Fig. A 3.2 Basic flow diagram for Model Identification 图A 3.2模型辨识的基本流程图

开始
设计工厂阶跃测试/伪随机二进制序列测试
AIDA数据生成器（测试数据收集并生成AIDA输入文件）
在AIDA中导入数据文件
选择模型输入和输出
执行预拟合FIR模型
拟合数据：估计模型参数
模型拟合度分析验证
检查模型是否可用
响应模型和可测量干扰模型的.TXT文件（AIDA模型）
AIDA存档

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原文：
Column Tray Loading (CTL):
This module calculates loading conditions in a distillation column. The calculated values can be used for information or for control purpose as a part of APC strategy for protection against flooding.
Constraint Pusher:
This algorithm is an online closed loop single variable optimization technique.
Pressure Compensated Temperature (PCT):
The composition of a liquid on a tray of a column can often be related to the temperature and pressure on that tray. The module is used in APC strategies for a distillation columns e.g. for cut point control.
Additional Modules:
Up time monitoring of control applications, signal filter for advanced rejection of noise from control signals etc.
In Yokogawa DCS, COAST modules run under FCS. For details, user shall refer to COAST module manual and project documentation.

Exarqe: Robust Quality Estimator:

This package is for robust and high-sustained accuracy inferred measurements. This package some times also called as “soft sensor” for providing analytical/quality related information of chemicals.
An inferred measurements is a Calculated Variable (CV) based on selected simple measurements (temperature, pressure, flow….) used to predict the current value of a critical product property or a complex process variable, when it can not be measured online but infrequently, with significant delay or not reliably. In typical application, RQE provides a calculated process value for a closed loop control purpose. RQE is particularly suited for applications in combination with Exasmoc APC strategies as shown in figure 3.0a.
Exarqe has an offline design tool, which finally creates Exarqe online file, which runs on Exasmoc station. For the details user shall refer Exarqe manual and project documentation.

A3.1 Basic Flow Diagram for building Exasmoc controller

The basic flow diagrams explained below would provide users to understand basic steps on how Exasmoc online controller is created for the APC project. Further it intends to give a feel of the SMOC-PC (Offline development tool) for the users who are not accustomed to the use of SMOC offline design and simulation package. The detailed information is available in respective manuals.
Start
Design Plant Step Test/ Pseudo Random Binary Sequence Test
AIDA Data Generator (Test Data Collection & generation of input file for AIDA)
Import Data File in AIDA
Select Model Inputs & Outputs
Perform Pre Fit Estimate FIR Model
Fit Data : Estimate Model Parameter
Analyse Fit for Model Validation
Check Model Adequacy
.TXT File (AIDA Model) for Action Model & Measured Disturbance Model
AIDA Archive

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2017.3.29