Documentation |
Replace or update Control Design Blocks in Generalized LTI model
Mnew = replaceBlock(M,Block1,Value1,...,BlockN,ValueN)
Mnew = replaceBlock(M,blockvalues)
Mnew = replaceBlock(...,mode)
Mnew = replaceBlock(M,Block1,Value1,...,BlockN,ValueN) replaces the Control Design Blocks Block1,...,BlockN of M with the specified values Value1,...,ValueN. M is a Generalized LTI model or a Generalized matrix.
Mnew = replaceBlock(M,blockvalues) specifies the block names and replacement values as field names and values of the structure blockvalues.
Mnew = replaceBlock(...,mode) performs block replacement on an array of models M using the substitution mode specified by the string mode.
M |
Generalized LTI model, Generalized matrix, or array of such models. |
Block1,...,BlockN |
Names of Control Design Blocks in M. The replaceBlock command replaces each listed block of M with the corresponding values Value1,...,ValueN that you supply. If a specified Block is not a block of M, replaceBlock that block and the corresponding value. |
Value1,...,ValueN |
Replacement values for the corresponding blocks Block1,...,BlockN. The replacement value for a block can be any value compatible with the size of the block, including a different Control Design Block, a numeric matrix, or an LTI model. If any value is [], the corresponding block is replaced by its nominal (current) value. |
blockvalues |
Structure specifying blocks of M to replace and the values with which to replace those blocks. The field names of blockvalues match names of Control Design Blocks of M. Use the field values to specify the replacement values for the corresponding blocks of M. The replacement values may be numeric values, Numeric LTI models, Control Design Blocks, or Generalized LTI models. |
mode |
String specifying the block replacement mode for an input array M of Generalized matrices or LTI models. mode can take the following values:
When the input M is a single model, '-once' and '-batch' return identical results. Default: '-once' |
This example shows how to replace a tunable PID controller (ltiblock.pid) in a Generalized LTI model by a pure gain, a numeric PI controller, or the current value of the tunable controller.
Create a Generalized LTI model of the following system:
where the plant $$G\left(s\right)=\frac{\left(s-1\right)}{{\left(s+1\right)}^{3}}$$, and C is a tunable PID controller.
G = zpk(1,[-1,-1,-1],1); C = ltiblock.pid('C','pid'); Try = feedback(G*C,1)
Replace C by a pure gain of 5.
T1 = replaceBlock(Try,'C',5);
T1 is a ss model that equals feedback(G*5,1).
Replace C by a PI controller with proportional gain of 5 and integral gain of 0.1.
C2 = pid(5,0.1); T2 = replaceBlock(Try,'C',C2);
T2 is a ss model that equals feedback(G*C2,1).
Replace C by its current (nominal) value.
T3 = replaceBlock(Try,'C',[]);
T3 is a ss model where C has been replaced by getValue(C).
This example shows how to sample a parametric model of a second-order filter across a grid of parameter values using replaceBlock.
Consider the second-order filter represented by:
Sample this filter at varying values of the damping constant and the natural frequency . Create a parametric model of the filter by using tunable elements for and .
wn = realp('wn',3); zeta = realp('zeta',0.8); F = tf(wn^2,[1 2*zeta*wn wn^2])
F = Generalized continuous-time state-space model with 1 outputs, 1 inputs, 2 states, and the following blocks: wn: Scalar parameter, 5 occurrences. zeta: Scalar parameter, 1 occurrences. Type "ss(F)" to see the current value, "get(F)" to see all properties, and "F.Blocks" to interact with the blocks.
F is a genss model with two tunable Control Design Blocks, the realp blocks wn and zeta. The blocks wn and zeta have initial values of 3 and 0.8, respectively.
Sample F over a 2-by-3 grid of (wn, zeta) values.
wnvals = [3;5]; zetavals = [0.6 0.8 1.0]; Fsample = replaceBlock(F,'wn',wnvals,'zeta',zetavals);
Fsample is a 2-by-3 array of state-space models. Each entry in the array is a state-space model that represents F evaluated at the corresponding (wn, zeta) pair. For example, Fsample(:,:,2,3) has wn = 5 and zeta = 1.0.
Examine the step response of Fsample.
stepplot(Fsample)
The step response plots show the variation in the natural frequency and damping constant across the six models in the array Fsample.
You can set the SamplingGrid property of the model array to help keep track of which set of parameter values corresponds to which entry in the array. To do so, create a grid of parameter values that matches the dimensions of the array. Then, assign these values to Fsample.SamplingGrid with the parameter names.
[wngrid,zetagrid] = ndgrid(wnvals,zetavals); Fsample.SamplingGrid = struct('wn',wngrid,'zeta',zetagrid);
When you display Fsample, the parameter values in Fsample.SamplingGrid are displayed along with the each transfer function in the array.