Filter data using Butterworth filters.
Syntax
zf = idfilt(z,ord,Wn)
[zf,thf] = idfilt(z,ord,Wn,hs)
Description
idfilt computes a Butterworth filter of order ord and filters all columns of the data matrix
z = [y u]
through this filter.
If hs is not specified and Wn contains just one element, a low pass filter with cutoff frequency Wn (measured as a fraction of the Nyquist frequency) is obtained. If hs =' high' a high pass filter with this cutoff frequency is obtained instead.
If Wn = [Wnl Wnh] is a vector with two elements, a filter (of order 2*ord) with passband between Wnl and Wnh is obtained is hs is not specified. If
hs = 'stop' a bandstop filter with stop band between these two frequencies is obtained instead.
The output argument thf is the filter given in the theta format.
It is common practice in identification to select a frequency band where the fit between model and data is concentrated. Often this corresponds to bandpass filtering with a pass band over the interesting breakpoints in a Bode diagram.
If ord is a positive integer, a non-causal, zero-phase filter is used for the filtering. If ord is a negative integer, a causal filter (of order abs(ord)) is used instead.
Algorithm
The used filter is the same as butter in the Signal Processing Toolbox would give. Also, the zero-phase filter is equivalent to filtfilt in that toolbox.
References
Ljung (1987), Chapter 13.
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