Option set for
options = ssregestOptions;
Create an option set for
ssregest that fixes the value of the initial states to
'zero'. Also, set the
opt = ssregestOptions('InitialState','zero','Display','on');
Alternatively, use dot notation to set the values of
opt = ssregestOptions; opt.InitialState = 'zero'; opt.Display = 'on';
comma-separated pairs of
the argument name and
Value is the corresponding value.
Name must appear inside quotes. You can specify several name and value
pair arguments in any order as
opt = ssregestOptions('InitialState','zero')fixes the value of the initial states to zero.
'ARXOrder'— ARX model orders
'auto'(default) | matrix of nonnegative integers
ARX model orders, specified as a matrix of nonnegative integers
nb nk]. The
max(ARXOrder)+1 must be greater
than the desired state-space model order (number of states). If you
specify a value, it is recommended that you use a large value for
To learn more about ARX model orders, see
'RegularizationKernel'— Regularizing kernel
Regularizing kernel used for regularized estimates of the underlying ARX model, specified as one of the following values:
'TC' — Tuned and correlated kernel
'SE' — Squared exponential
'SS' — Stable spline kernel
'HF' — High frequency stable spline
'DI' — Diagonal kernel
'DC' — Diagonal and correlated
For more information, see .
'Reduction'— Options for model order reduction
Options for model order reduction, specified as a structure with the following fields:
State elimination method. Specifies how to eliminate the weakly coupled states (states with smallest Hankel singular values). Specified as one of the following values:
|Discards the specified states and alters the remaining states to preserve the DC gain.|
|Discards the specified states without altering the remaining states. This method tends to product a better approximation in the frequency domain, but the DC gains are not guaranteed to match.|
Absolute and relative error tolerance for stable/unstable decomposition.
Positive scalar values. For an input model G with
unstable poles, the reduction algorithm of
ssregest first extracts the stable
dynamics by computing the stable/unstable decomposition G → GS + GU. The
control the accuracy of this decomposition by ensuring that the frequency
responses of G and GS + GU differ by no more than
Increasing these tolerances helps separate nearby stable and unstable
modes at the expense of accuracy. See
0; RelTol = 1e-8
Offset for the stable/unstable boundary. Positive scalar value. In the stable/unstable decomposition, the stable term includes only poles satisfying
Re(s) < -Offset * max(1,|Im(s)|) (Continuous
|z| < 1 - Offset (Discrete
Increase the value of
treat poles close to the stability boundary as unstable.
options— Option set for
Estimation options for
ssregest, returned as an
ssregestoptions option set.
 T. Chen, H. Ohlsson, and L. Ljung. “On the Estimation of Transfer Functions, Regularizations and Gaussian Processes - Revisited”, Automatica, Volume 48, August 2012.