Main Content

Linear Grey-Box Models

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

If you understand the physics of your system and can represent the system using ordinary differential or difference equations (ODEs) with unknown parameters, then you can use System Identification Toolbox™ commands to perform grey-box modeling. Grey-box model ODEs specify the mathematical structure of the model explicitly, including couplings between parameters. Grey-box modeling is useful when you know the relationships between variables, constraints on model behavior, or explicit equations representing system dynamics.

You can represent a linear grey-box model using an idgrey object, which requires that you write a function to describe the linear dynamics in state-space form. For more information, see Estimate Linear Grey-Box Models.

Functions

expand all

greyestEstimate ODE parameters of linear grey-box model
greyestOptionsOption set for greyest
idgreyLinear ODE (grey-box model) with identifiable parameters
pemPrediction error minimization for refining linear and nonlinear models
initSet or randomize initial parameter values
getpvecObtain model parameters and associated uncertainty data
setpvecModify values of model parameters
getparObtain attributes such as values and bounds of linear model parameters
setparSet attributes such as values and bounds of linear model parameters
findstatesEstimate initial states of model
findstatesOptionsOption set for findstates

Topics

Featured Examples