灰盒模型估计
如果您了解系统的物理特性，并且可以使用带有未知参数的常微分方程或差分方程 (ODE) 来表示系统，则可以使用 System Identification Toolbox™ 命令执行灰盒建模。灰盒模型 ODE 明确指定模型的数学结构，包括参数之间的耦合。当您了解变量之间的关系、模型行为的约束或表示系统动态特性的显式方程时，灰盒建模是很有用的。
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灰盒建模基础知识
- 线性和非线性灰盒建模
如果您了解系统的物理原理，就可以对线性或非线性的灰盒模型进行估计。 - Identifying State-Space Models with Separate Process and Measurement Noise Descriptions
An identified linear model is used to simulate and predict system outputs for given input and noise signals. - Loss Function and Model Quality Metrics
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
The estimation report contains 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. - Estimate Coefficients of ODEs to Fit Given Solution
Estimate model parameters using linear and nonlinear grey-box modeling. - Building Structured and User-Defined Models Using System Identification Toolbox
This example shows how to estimate parameters in user-defined model structures.
线性灰盒模型
- Estimate Linear Grey-Box Models
How to define and estimate linear grey-box models at the command line. - Estimate Continuous-Time Grey-Box Model for Heat Diffusion
This example shows how to estimate the heat conductivity and the heat-transfer coefficient of a continuous-time grey-box model for a heated-rod system. - Estimate Discrete-Time Grey-Box Model with Parameterized Disturbance
This example shows how to create a single-input and single-output grey-box model structure when you know the variance of the measurement noise. - 使用零点/极点/增益参数估计模型
本示例演示了如何对由极点、零点和增益参数化的一款模型进行估计。该示例需要使用 Control System Toolbox™ 软件。 - Estimate State-Space Models with Structured Parameterization
Structured parameterization lets you exclude specific parameters from estimation by setting these parameters to specific values.
非线性灰盒模型
- 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.
精选示例
车辆动力学系统建模
此示例展示了车辆动力学的非线性灰盒建模。
空气动力学飞行体建模
本示例展示了对一个大型且复杂的非线性系统进行灰盒建模的过程。
Modeling an Industrial Robot Arm
Grey-box modeling of the dynamics of an industrial robot arm.
Represent Nonlinear Dynamics Using MATLAB File for Grey-Box Estimation
Construct, estimate, and analyze nonlinear grey-box models.
Two Tank System: C MEX File Modeling of Time-Continuous SISO System
Perform IDNLGREY modeling based on C MEX model files.
Three Ecological Population Systems: MATLAB and C MEX File Modeling of Time-Series
Create nonlinear grey box time series models.
Narendra-Li Benchmark System: Nonlinear Grey Box Modeling of a Discrete-Time System
Identify the parameters of a complex yet artificial nonlinear discrete-time system with one input and one output.
Friction Modeling: MATLAB File Modeling of Static SISO System
Grey-box modeling of a static single-input, single-output system using a MATLAB function as the ODE file.
Signal Transmission System: C MEX File Modeling Using Optional Input Arguments
Provide optional input arguments to IDNLGREY models.
Dry Friction Between Two Bodies: Parameter Estimation Using Multiple Experiment Data
Estimate parameters of a nonlinear grey box model using multiple experiment data.
Industrial Three-Degrees-of-Freedom Robot: C MEX File Modeling of MIMO System Using Vector/Matrix Parameters
Design C-MEX model files that involve scalar, vector, and matrix parameters.
Non-Adiabatic Continuous Stirred Tank Reactor: MATLAB File Modeling with Simulations in Simulink
Include and simulate an IDNLGREY model in Simulink®.
Classical Pendulum: Some Algorithm-Related Issues
How the estimation algorithm choices may impact the results for a nonlinear grey box model estimation.
