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Multivariable bilinear transform of frequency (s or z).
[ab,bb,cb,db] = bilin(a,b,c,d,ver,Type,aug) [ssb] = bilin(ss,ver,Type,aug)
Description
Bilin
computes the effect on a system of the frequency-variable substitution,
Ver
denotes the transformation direction:
Ver= 1
, forward transform Ver=-1
, inverse transform Bilin
computes several state-space bilinear transformations such as Tustin, prewarped Tustin, etc., based on the Type
you select:
Type = 'Tustin'
, Tustin transform: aug =
T, the sampling period.
Type = 'P_Tust'
, prewarped Tustin: aug = [
T ]
,
Type = 'BwdRec'
, backward rectangular: aug =
T, the sampling period.
Type = 'FwdRec'
, forward rectangular: aug =
T, the sampling period.
Type = 'S_Tust'
, shifted Tustin: aug =
[T h], is the "shift" coefficient.
Type = 'S_ftjw'
, shifted jaug =
[p2 p1].
Type = 'G_Bilin'
, general bilinear: aug =
Examples
Consider the following continuous-time plant (sampled at 20 Hz)
bilin
transformations for the sampled plant:
ss = mksys(a,b,c,d); %use system data structure [sst] = bilin(ss,1,'Tustin',0.05); [ssp] = bilin(ss,1,'P_Tust',[0.05 40]); [ssb] = bilin(ss,1,'BwdRec',0.05); [ssf] = bilin(ss,1,'FwdRec',0.05); w = logspace(-2,3,100) %frequency svt = dsigma(sst,0.05,w); svp = dsigma(ssp,0.05,w); svb = dsigma(ssb,0.05,w); svf = dsigma(ssf,0.05,w); .
Figure 1-3: Comparison of 4 Bilinear Transforms.
you can generate the continuous and discrete singular value Bode plots as shown in the Figure 1-3. Note that the Nyquist frequency is at 20
Algorithm
bilin
employs the state-space formulae in [3]:
![]() | balmr, schmr | blkrsch, cschur | ![]() |