Nonparametric Model Estimation Methods (System Identification Toolkit)

You can describe linear time-invariant models with transfer functions or by using the impulse response or frequency response of the system. The impulse response and frequency response are two ways of estimating a nonparametric model. The impulse response reveals the time-domain properties of the system, such as time delay and damping. The frequency response reveals the frequency-domain properties, such as the natural frequency of the system.

Nonparametric model estimation is more efficient, but often less accurate, than parametric estimation. However, you can use a nonparametric model estimation method to obtain useful information about a system before applying parametric model estimation. For example, you can use nonparametric model estimation to determine whether the system requires preconditioning, what the time delay of the system is, what model order to select, and so on. You also can use nonparametric model estimation to verify parametric models. For example, you can compare the Bode plot of a parametric model with the frequency response of the nonparametric model.

You can use the least squares and correlation analysis methods to estimate the impulse response of a dynamic system. You can use the spectral analysis method to estimate the frequency response of a dynamic system.