User`s guide

Identifying State-Space Models
You can specify additional property-value pairs similar to the
free-parameterization case, as described in “How to Estimate
Free-Parameterization State-Space M odels” on page 3-90.
For information about validating your model, see “Overview of Model
Validation and Plots” on page 8-2.
How to Estimate State-Space Models with Structured
Parameterization
• “What Is Structured Parameterization?” on page 3-93
• “Specifying the State-Space Structure” on page 3 -94
• “Are Grey-Box Models Similar to State-Space Models with Structured
Parameterization?” on page 3-96
• “Example – E stim ating Structured Discrete-T ime Sta te-Space Models”
on page 3-96
• “Example – Estimating Structured Con tinuous-Time State-Space Models”
on page 3-97
What Is Structured Parameterization?
Structured parameterization lets you exclude specific parameters from
estimation by setting these parameters to specific values. This approach is
useful when you can derive state-space matrices from physical principles and
provide initial parameter values based on physical insight. You can use this
approach to discover wh at happe ns if y ou fixspecific parameter values or if
you free certain parameters.
In the case of structured parameterization, there are two stages to the
estimation procedure:
1 Using the idss command to specify the structure of the state-space
matrices and the initial values of the free parameters
2 Using the pem estimation command to estimate the free model parameters
3-93