原文：
Model Reduction 模型降階 采用最佳途徑將一個高階（或非參數(shù)）模型降為更低階模型的過程样眠。
**MV **操作變量冷尉。
Noise 噪聲 干擾真實或原始信號的某一信號或某信號的組成部分。不可測量的輸入影響了過程行為。信號的不確定性或隨機性部分吟孙。
**Non-parametric Model **非參數(shù)模型 模型不由特定的模型結(jié)構(gòu)所限制俐末。
**Overlay ** 覆蓋 多個趨勢（響應(yīng)）鋪設(shè)在彼此的頂部或同一坐標(biāo)軸上。
**Parametric Model **參數(shù)模型 模型的結(jié)構(gòu)被定義庄蹋，且由固定數(shù)目的參數(shù)來定義模型瞬内。
**PCTP ** 過程控制技術(shù)包。.
**PRBS ** 偽隨機二進制序列限书。也被稱為PRBNS虫蝶，其中N是噪聲（noise），S是信號（signal）倦西。
**Prediction **預(yù)測 模型輸入一組輸入變量后能真，試圖模擬真實信號響應(yīng)的過程。
**Prefilter **預(yù)濾波器 當(dāng)信號被用于模型估計練習(xí)前時，濾波器應(yīng)用于其中一個或所有信號粉铐。PVR 過程變量探索器疼约。
QMI 質(zhì)量測量儀或性能分析儀。
Ramp 一個積分過程或過程變量蝙泼。
Regression 回歸 回歸是用于表征當(dāng)輸入變量變化時程剥，哪個輸出變量產(chǎn)生變化的方式。最優(yōu)回歸是通過使用最小二乘法最小化預(yù)測輸出與實際誤差得到的汤踏。
**Residual **殘差 代表了模型擬合后輸出的未知變化织鲸。它是預(yù)測輸出與實際輸出之間的偏差。也被稱為誤差茎活。
**RQE ** 穩(wěn)健質(zhì)量預(yù)估器昙沦。
Sample Period 采樣周期 連續(xù)信號連續(xù)采樣周期之間的時間間隔。
Settling-time 穩(wěn)態(tài)時間 當(dāng)輸入改變時载荔，過程/模型重新進入穩(wěn)態(tài)所需要的時間盾饮。
Signal-to-Noise Ratio 信噪比 信號部分與噪聲部分的比例。信號中噪聲含量越多懒熙，信噪比越低丘损。SNR = σy /σn 其中σy是信號y（也可以是x）的測量值，σn是噪聲含量工扎。
Simulation 仿真 確定性預(yù)測 其中沒有基于歷史輸出測量值的反饋用于更新預(yù)測徘钥。
**SISO **單輸入單輸出。
**SMOC **殼牌多變量優(yōu)化控制肢娘。
**State-space **狀態(tài)空間 一個用于定義系統(tǒng)的抽象數(shù)學(xué)空間呈础。在動態(tài)系統(tǒng)中，根據(jù)系統(tǒng)狀態(tài)系統(tǒng)可被建模為一組一階微分（差分）方程橱健。
**Stationary **穩(wěn)定 信號到達穩(wěn)態(tài)是在一個平均值周圍浮動的而钞。變量與非穩(wěn)定或漂移相反的，是不在固定平均值周圍浮動拘荡。
Steady-State 穩(wěn)態(tài) 當(dāng)一個過程變量不隨時間變化時的狀態(tài)臼节。
**Step Response **階躍響應(yīng) 對自變量施加一單位階躍，獲得的因變量的響應(yīng)珊皿。
Step Testing 階躍測試 通過給輸入（自變量）一個階躍從而給過程擾動网缝。
Tag 位號 過程變量標(biāo)簽。偶爾也稱為點蟋定。
Variance 方差 方差描述了數(shù)值與期望值（或平均值）的差異粉臊。它是標(biāo)準(zhǔn)差的平方。這里指的數(shù)值既可以是一個直接的測量值驶兜，也可以是測量值的函數(shù)维费。
**White Noise **白噪聲 與本身不相關(guān)（無顯著自相關(guān)系數(shù) lags>0）且完全不可預(yù)測的時間序列（或序列）果元。
Zero-order Hold 零階保持 當(dāng)連續(xù)信號進行采樣時促王，模擬信號在一個采樣間隔點進行采樣犀盟，并且一直“保持”該值直到下一個采樣時間。因為零階保持的緣故蝇狼，在輸入輸出系統(tǒng)的情況下當(dāng)輸入變量變化時阅畴，至少需要一個采樣周期輸出變量才會變化。
原文：
Model Reduction The process of reducing a higher-order (or non-parametric) model into a lower order model in the best way.
MV Manipulated Variable.
Noise Any signal or a component of a signal that interferes with the true or original signal. Unmeasured inputs affecting process behavior. The non-deterministic or stochastic component of a signal.
**Non-parametric Model **A model not restricted by a specific model structure.
Overlay The laying of multiple trends (responses) on top of each other or on the same plot axes.
Parametric Model A model whose structure is set and is defined by a fixed number of parameters.
**PCTP ** Process Control Technology Package.
PRBS Pseudo Random Binary Sequence. Also referred to as PRBNS with N for noise and S for signal.
Prediction The response of a model to a set of inputs that tries to emulate a true signal.
Prefilter Filter applied to one or all of the signals before they are used in a model estimation exercise.
**PVR ** Process Variable Retriever.
QMI Quality Measuring Instrument or property analyzer.
Ramp An integrating process or process variable.
Regression Regression is used to characterize the manner by which an output variable changes as input variables changes. The best regression is obtained using a least-squares minimization of the output prediction version actual errors.
Residual Represents the unexplained variation of an output after fitting of a model. It is the difference between the actual output and the predicted output. Also known as error.
**RQE ** Robust Quality Estimator.
**Sample Period ** The time interval between consecutive samplings of continuous signal.
Settling-time Time taken by a process/model to become steady after an input change to it was made.
**Signal-to-Noise Ratio ** The ratio of the content of a signal to the noise content in it. The higher the noise level in a signal, the lower this ratio. SNR = σy /σn where σy is a measure of the content of the signal y (sometimes x) and σn is the content of the noise.
Simulation The deterministic prediction, where no feedback based on past measurements of
the output is used in updating the prediction.
SISO Single-Input Single-Output.
SMOC Shell Multivariable Optimizing Control.
State-space An abstract mathematical space used to define a system. In a dynamic system,
the system can be modeled as a set of first order differential (difference) equations in terms of the system states.
**Stationary **A stationary signal is one in which variation is around a mean value. The opposite of a non-stationary or drifting variable, in which variation is not around a fixed mean.
Steady-State The condition when a process variable is not changing with time.
Step Response The response of a dependent variable to a unit step change an independent variable.
**Step Testing **Perturbing a process using step changes in inputs (independents).
**Tag **A process variable label. Also referred to as point occasionally.
Variance Variance describes variability of a quantity about an expected (or mean) value. It is the square of the standard deviation. The quantity referred to can be a directly measured value or a function of measured values.
**White Noise **A time series (or sequence) that is completely unpredictable and therefore is uncorrelated with itself (no significant autocorrelation coefficients for lags > 0).
Zero-order Hold When a continuous signal is sampled, the analog signal is sampled at a sample interval and is “held” constant at that value until the next sampling instant. In the context of input-output systems, when an input change is made, the change usually takes at least one sampling interval before it shows up in the output because of zero-order hold.
2016/4/16
