Grey-Box-Modellschätzung
Schätzen von Koeffizienten linearer und nichtlinearer Differenzial-, Differenz- und Zustandsraumgleichungen
Wenn Sie die Physik Ihres Systems verstehen und das System mithilfe gewöhnlicher Differenzial- oder Differenzgleichungen (ODE) mit unbekannten Parametern darstellen können, können Sie die Befehle der System Identification Toolbox™ für die Grey-Box-Modellierung verwenden. Bei ODEs für Grey-Box-Modelle wird die mathematische Struktur des Modells explizit festgelegt, einschließlich der Kopplungen zwischen den Parametern. Die Grey-Box-Modellierung ist nützlich, wenn Ihnen die Beziehungen zwischen Variablen, Randbedingungen des Modellverhaltens oder explizite Gleichungen, die die Systemdynamik darstellen, bekannt sind.
Funktionen
Themen
Grundlagen der Grey-Box-Modellierung
- Linear and Nonlinear Grey-Box Modeling
If you understand the physics of your system, you can estimate linear or nonlinear grey-box models. - 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.
Lineare Grey-Box-Modelle
- 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. - Estimate Model Using Zero/Pole/Gain Parameters
This example shows how to estimate a model that is parameterized by poles, zeros, and gains. - Estimate State-Space Models with Structured Parameterization
Structured parameterization lets you exclude specific parameters from estimation by setting these parameters to specific values.
Nicht lineare Grey-Box-Modelle
- 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.