子控制器
? INACTIVE
子控制器執(zhí)行時進(jìn)行數(shù)據(jù)監(jiān)視和模型更新。DCS沒有MV輸出。
? ACTIVE
基于DCS的BRC和ERC在運(yùn)行中，同時DCS PID等在遠(yuǎn)程模式下接受來自Exasmoc計(jì)算的MV。
計(jì)算
? INACTIVE
更新輸入數(shù)據(jù)并進(jìn)行計(jì)算，但DCS沒有輸出。
? ACTIVE
更新輸入數(shù)據(jù)，計(jì)算完畢，結(jié)果輸出到DCS。
A3搭建模塊概述
本節(jié)的目的是：在用戶開始使用本說明手冊用于Exasmoc在線控制器對工廠進(jìn)行操作之前，向用戶概述APC整體項(xiàng)目工程。
Exasmoc由以下模塊組成：
AIDAPro
AIDA Pro（先進(jìn)辨識和數(shù)據(jù)分析）是一個基于Windows的軟件包，用于預(yù)估流程單元的線性動態(tài)模型。AIDAPro是離線先進(jìn)控制軟件包PCTP（過程控制技術(shù)包）的一個軟件小包。需要一個處理單元的線性動態(tài)模型來實(shí)現(xiàn)Exasmoc的模型預(yù)測控制應(yīng)用程序。
在工廠數(shù)據(jù)的基礎(chǔ)上推導(dǎo)工廠的動態(tài)模型稱為辨識。在采集過程數(shù)據(jù)時，給定采樣周期（通常為1分鐘），對感興趣單元執(zhí)行工廠測試。采集的數(shù)據(jù)包括工廠操作（過程輸入或自變量）的設(shè)定點(diǎn)，受過程輸入變化影響的工廠運(yùn)行變量，未來先進(jìn)控制方案中調(diào)節(jié)或優(yōu)化的目標(biāo)（過程輸出或因變量），以及提供當(dāng)前工廠條件信息的一些相關(guān)變量，以幫助獲得更準(zhǔn)確的模型（可測量的干擾變量）。
例如，典型的獨(dú)立變量是：
-PID控制器設(shè)定點(diǎn)（流量，溫度和壓力），
- 控制閥閥位。
典型的因變量是： - 流程性能或約束測量值（流量，溫度，壓力，在線分析儀測量值，閥位），
計(jì)算變量（例如估計(jì)的測量值）。
典型的干擾變量是： - 進(jìn)料速率; 進(jìn)料溫度，進(jìn)料質(zhì)量，
- 與在線分析儀測量值相關(guān)的溫度或壓力，
- PID控制器的過程測量值。
工廠測試涉及到多個感興趣的獨(dú)立變量時，需要一個接一個分開測試。選擇并監(jiān)控階躍大小和重復(fù)次數(shù)，以便在最小化工廠擾動的同時實(shí)現(xiàn)期望的階躍幅度以獲得有用的模型。根據(jù)應(yīng)用和操作條件（階躍測試，偽隨機(jī)二進(jìn)制序列（PRBS）），可將不同類型的干擾信號用于工廠測試。
原文：
Sub-Controller
? INACTIVE
Data monitoring and Model is updated during execution of Sub Controller. There is no MV output to DCS.
? ACTIVE
DCS based BRC and ERC in operation also DCS PID’s etc in a remote mode to accept MV’s from Exasmoc Calculation
Calculation
? INACTIVE
Input data is updated and calculation is done, but there is no output to DCS.
? ACTIVE
Input data is updated, calculation is done, and the result is output to DCS.
A3. Overview of Building Blocks
The purpose of this section is to provide the user an overview of the total APC project engineering before user start making use of this instruction manual for operating his/her plant with Exasmoc online controller.
Exasmoc is composed of following functionalities:
AIDAPro
AIDA Pro(Advanced Identification and Data Analysis) is a Windows based software package used to estimate a linear dynamic model for a process unit. AIDAPro is one package of Off-line Advanced Control general package PCTP (Process Control technology Package).A linear dynamic model of a process unit is required to implement a Model Predictive control application for Exasmoc.
Deriving a dynamic model for a plant on the basis of plant data is called identification. A plant test is performed on the unit of interest while process data is collected at a given sampling period, typically one-minute. Collected data include the set-point of the plant operating handles (the process inputs, or independent variables), the plant operating variables that are affected by changes in the process inputs and for which there are regulation or optimization objectives in the future advanced control scheme (the process outputs, or dependent variables), and a number of associated variables that provide information on the current plant conditions and help obtain a more accurate model (the measured disturbance variables ).
For example, typical independent variables are:
-PID controller set points (flow, temperature, and pressure),
-Desired control valves position.
Typical dependent variables are:
-Process performance or constraint measurements (flow, temperature, pressure, on-line Analyzer measurement, valve position),
Calculated variable (e.g. inferred measurement).
Typical disturbance variables are:
-Feed rate; feed temperature, feed quality,
-Temperature or pressure correlated to on-line Analyzer measurement,
-Process measurement of a PID controller.
The plant test involves stepping the independent variables of interest, multiple times, generally one after the other. The step size and number of repetitions is selected and monitored closely, in order to minimize the plant disturbances, while achieving the desired level of excitation to obtain a useful model. Different types of disturbance signals can be used for plant tests depending on the application and conditions of operation (step tests, Pseudo Random Binary Sequence (PRBS)).
2017.3.27
