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モデル タイプとその他の変換
関数
idfrd | Frequency response data or model |
idpoly | Polynomial model with identifiable parameters |
idtf | Transfer function model with identifiable parameters |
idss | State-space model with identifiable parameters |
canon | 正準状態空間実現 |
balred | モデル次数の低次元化 |
noisecnv | Transform identified linear model with noise channels to model with measured channels only |
translatecov | Translate parameter covariance across model transformation operations |
merge | Merge estimated models |
append | 入力と出力を追加して、モデルをグループ化する |
noise2meas | Noise component of model |
absorbDelay | むだ時間を z = 0 または移相シフトでの極に置き換える |
chgTimeUnit | 動的システムの時間単位の変更 |
chgFreqUnit | 周波数応答データ モデルの周波数単位の変更 |
fdel | 周波数応答データ (FRD) モデルから指定したデータを削除 |
stack | 配列次元と共にモデルまたはモデル配列をスタックして、モデル配列を作成する |
ss2ss | 状態空間モデルの状態座標変換 |
例および使用方法
- Transforming Between Linear Model Representations
Converting between state-space, polynomial, and frequency-response representations.
- Reducing Model Order Using Pole-Zero Plots
You can use pole-zero plots of linear identified models to evaluate whether it might be useful to reduce model order. When confidence intervals for a pole-zero pair overlap, this overlap indicates a possible pole-zero cancellation.
- Create and Plot Identified Models Using Control System Toolbox Software
Identify models and use the Linear System Analyzer to plot the models.
概念
- Using Identified Models for Control Design Applications
Using System Identification Toolbox™ models with Control System Toolbox™ software.
- Subreferencing Models
Creating models with subsets of inputs and outputs from multivariable models at the command line.
- 状態空間実現
モード正準形式、コンパニオン正準形式、可観測正準形式、可制御正準形式の状態空間モデル。
- Concatenating Models
Horizontal and vertical concatenation of model objects at the command line.
- Merging Models
How to merge models to obtain a single model with parameters that are statistically weighed means of the parameters of the individual models.
- Treating Noise Channels as Measured Inputs
Convert noise channels to measured channels and include the variance of the innovations.