Grey-Box Model Estimation

Estimate coefficients of linear and nonlinear differential, difference and state-space equations

Functions

`greyest`	Linear grey-box model estimation
`nlgreyest`	Estimate nonlinear grey-box model parameters
`idgrey`	带有可识别参数的线性ode（灰色框模型）
`艾德格里`	非线性灰色框
`pem`	预测误差最小化线性和非线性模型

`findstates`	估计模型的初始状态
`init`	Set or randomize initial parameter values
`getinit`	Values of`艾德格里`model initial states
`setinit`	设置初始状态`艾德格里`model object
`getpar`	Parameter values and properties of`艾德格里`模型参数
`setpar`	Set initial parameter values of`艾德格里`model object
`getpvec`	Obtain model parameters and associated uncertainty data
`setpvec`	Modify values of model parameters
`sim`	Simulate response of identified model

Estimate Linear Grey-Box Models
如何在命令行中定义和估计线性灰色模型。
Estimate Continuous-Time Grey-Box Model for Heat Diffusion
该示例显示了如何估计加热杆系统连续时灰盒模型的热电导率和热传递系数。
Estimate Discrete-Time Grey-Box Model with Parameterized Disturbance
此示例显示了当您知道测量噪声的方差时，如何创建单输入和单输出灰色模型结构。
估计ODE的系数以适合给定溶液
Estimate model parameters using linear and nonlinear grey-box modeling.
Estimate Model Using Zero/Pole/Gain Parameters
此示例显示了如何估计由极点，零和收益参数化的模型。
Estimate Nonlinear Grey-Box Models
How to define and estimate nonlinear grey-box models at the command line.
Creating IDNLGREY Model Files
This example shows how to write ODE files for nonlinear grey-box models as MATLAB and C MEX files.
Estimate State-Space Models with Structured Parameterization
结构化参数化让您通过将这些参数设置为特定值将特定参数从估计中排除。
Building Structured and User-Defined Models Using System Identification Toolbox™
This example shows how to estimate parameters in user-defined model structures.

Supported Grey-Box Models
Types of supported grey-box models.
Data Supported by Grey-Box Models
Types of supported data for estimating grey-box models.
选择IDGREY或IDNLGREY模型对象
Difference betweenidgrey和艾德格里用于表示灰色框模型对象的模型对象。
通过单独的过程和测量噪声描述识别状态空间模型
An identified linear model is used to simulate and predict system outputs for given input and noise signals.
损失功能和模型质量指标
Configure the loss function that is minimized during parameter estimation. After estimation, use model quality metrics to assess the quality of identified models.
Estimation Report
Theestimation reportcontains information about the results and options used for a model estimation.
Regularized Estimates of Model Parameters
Regularization is the technique for specifying constraints on the flexibility of a model, thereby reducing uncertainty in the estimated parameter values.