Fits~ Overview –Simulation-1

Plot Time Steps（图表时间步长）：直到此时刻的阶跃响应图（即每幅图的x轴为0~响应时间）。
Active Parametric Model（活跃参数模型）：指定要在后续分析中使用的拟合结果是根据参数模型拟合得到的FIR结果（F2P）还是来自数据的参数拟合（PAR）。
Column Headings（列标题）：输出。
Scale Factor（比例因子）：如果选择了标准化缩放，则输入的比例因子显示在输入位号名称旁边的新列中。比例因子是相应输入/中间位号的正常变化。
Row Headings（行标题）：输入/中间变量。
Show（显示）：如果选中，则相应的模型阶跃响应会显示在Overlay模型图上。
Color（颜色）：双击以修改模型图线颜色。
Name（名称）：模型源的名称。（FIR是FIR拟合结果; F2P是自FIR简化的参数模型; PAR是使用所选择数据集的参数模型拟合）
Input x Output（输入x输出）：选中单元格的对应Input（输入）和Output（输出）。
Gain（增益）：选中单元格对应的模型增益。
Model（模型）：模型类型—稳态或斜坡。
Fit Stat（拟合统计）：与输入输出关系相对应的Fit Stat（拟合统计）。
Output Fit Stat（输出拟合统计）：与整个输出相对应的Fit Stat（拟合统计）。
在Simulation（仿真）选项卡上，对每个模型，还有一个右键单击选项可停用模型。停用模型后将保留模型的拟合信息，但在仿真时将此模型当做零阶模型处理。可以通过这样看到这个具体模型对仿真做出的贡献。

仿真
Simulation（仿真）选项卡包括了拟合组中拟合结果的输出趋势和拟合中的模型输出预测（FIR，来自FIR的参数，以及来自数据的参数）。每个模型的性能可以通过预测与预测输出的匹配程度来确定。输入的趋势也可以在预测窗口中找到。
特定拟合的性能可以通过以下方式评估：
•Simulation（仿真）—仅基于模型确定部分的输出预测。它可以被认为是开环预测，没有对测量知识做出任何校正。请参阅第39页的“确定性预测（仿真）”。
•Error（误差）—误差是实际输出和预测输出（仅基于模型确定部分）之间的差异。如果误差是随机分布的，则模型可以被认为是良好的。请参阅第40页的“确定性仿真（误差）”。

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原文：
Plot Time Steps:Plot the step responses up to this time (that is, the xaxis for each plot is of the form 0 – Response time).
Active Parametric Model: Designates if the result of this fit to be used in subsequent analysis is the Parametric model fit to the FIR results (F2P) or the Parametric fit from data(PAR).
**Column Headings: **Outputs.
**Scale Factor: **If normalized scaling is selected, the scale factors for the inputs are displayed in a new column beside the input tag name. The scale factor is the normal change for the corresponding input/intermediate tag.
Row Headings: Inputs/Intermediates.
Show: If checked, the corresponding model step response is shown on the Overlay model plot.
Color: Double-click to modify the model plot line color.
Name:Name of the model source. (FIR is the FIR Fit result; F2P is the parametric model reduced from the FIR; PAR is the parametric model fit using the datasets selected)
Input x Output: Input and Output corresponding to the selected cell.
**Gain: **Model gain corresponding to the selected cell.
Model: Model type – stable or ramp.
**Fit Stat: **Fit Stat corresponding to the input output relationship.
**Output Fit Stat: **Fit Stat corresponding to the entire output.
There also is a right click option on each model to deactivate the model on the Simulation tab. Deactivating a model retains the model fit information but simulates as if there was a zero model in this model. This lets you see what contribution this specific model is making to the simulations.
Simulation
The Simulation tab consists of trends of the outputs of the fit group fit results and the output predictions from models in the fit (FIR, parametric from FIR, and parametric from data). The performance of each model can be determined by how closely a prediction matches the output being predicted. The trends of inputs are also available on the predictions window.
The performance of a particular fit can be assessed by:
**•Simulation – **A prediction of the output based only on the deterministic part of the model. It can be considered the open-loop prediction without any corrections made with measurements knowledge. Refer to “Deterministic Prediction (Simulation)” on page 39.
•Error – Errors are the difference between the actual output and the predicted output (based only on the deterministic part of the model). A model may be considered good if the errors are randomly distributed. Refer to “Deterministic Simulation (Error)” on page 40.

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2016.11.22