Robust Control Toolbox™

Fit frequency response data with state-space model

Syntax

• B = fitfrd(A,N) 
  B = fitfrd(A,N,RD) 
  B = fitfrd(A,N,RD,WT) 
  

Description

B = fitfrd(A,N) is a state-space object with state dimension N, where A is an frd object and N is a nonnegative integer. The frequency response of B closely matches the D-scale frequency response data in A.

A must have either 1 row or 1 column, although it need not be 1-by-1. B will be the same size as A. In all cases, N should be a nonnegative scalar.

B = fitfrd(A,N,RD) forces the relative degree of B to be RD. RD must be a nonnegative integer. The default value for RD is 0. If A is a row (or column) then RD can be a vector of the same size as well, specifying the relative degree of each entry of B. If RD is a scalar, then it specifies the relative degree for all entries of B. You can specify the default value for RD by setting RD to an empty matrix.

B = fitfrd(A,N,RD,WT) uses the magnitude of WT to weight the optimization fit criteria. WT can be a double, ss or frd. If WT is a scalar, then it is used to weight all entries of the error criteria (A-B). If WT is a vector, it must be the same size as A, and each individual entry of WT acts as a weighting function on the corresponding entry of (A-B).

Example

You can use the fitfrd command to fit D-scale data. For example, create D-scale frequency response data from a fifth-order system.

• sys = tf([1 2 2],[1 2.5 1.5])*tf(1,[1 0.1]); 
  sys = sys*tf([1 3.75 3.5],[1 2.5 13]); 
  omeg = logspace(-1,1); 
  sysg = frd(sys,omeg); 
  bode(sysg,'r-');
  
  
  

You can try to fit the frequency response D-scale data sysg with a first-order system, b1. Similarly, you can fit the D-scale data with a third-order system, b3.

• b1 = fitfrd(sysg,1); 
  b3 = fitfrd(sysg,3); 
  

Compare the original D-scale data sysg with the frequency responses of the first and third-order models calculated by fitfrd:

• b1g = frd(b1,omeg); 
  b3g = frd(b3,omeg); 
  bode(sysg,'r-',b1g,'k:',b3g,'b-.')
  
  
  

Limitations

Numerical conditioning problems arise if the state order of the fit N is selected to be higher than required by the dynamics of A.

See Also
fitmagfrd   Fit magnitude data with stable LTI model

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