Performing a model order reduction including initial conditions

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I've been attempting to reduce the order of a state space model, for example:
sys=ss(A,B,C,D)
sys_reduced=reduce(sys,10)
which works fine, but does anyone know how to calculate the initial conditions for this reduced system (assuming the initial system had initial conditions)
  2 Kommentare
Richard
Richard am 18 Jul. 2012
To answer my own question:
The function [ModelNew,g,T,Ti]=balreal(modelOld) gives a new model which has as many states as the old model BUT they are in decending order of importance. It also gives g which shows how important each state is and T which transforms the old model into the new WHICH CAN ALSO BE USED TO TRANSFORM THE INITIAL CONDITIONS, Ti is the reverse transform
newIntialConditions=T*OldIntialConditions;
modred can then be used to reduce the model order to whatever you want
ReducedModel=modred(BallencedModel,ReduceStatesTo:NumberOfStatesInOldModel);
The initial conditions must of course also be trimmed to the right number of states
Kaustubha Govind
Kaustubha Govind am 18 Jul. 2012
Richard: Thanks for coming back to the forum with your answer. Could you perhaps post this as an answer instead of as a comment. Feel free to accept your own answer.

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Richard
Richard am 26 Feb. 2013
To answer my own question:
The function [balancedModel,g,T,Ti]=balreal(modelOld) gives a new model which has as many states as the old model BUT they are in decending order of importance. It also gives g which shows how important each state is and T which transforms the old model into the new WHICH CAN ALSO BE USED TO TRANSFORM THE INITIAL CONDITIONS, Ti is the reverse transform
newIntialConditions=T*OldIntialConditions;
modred can then be used to reduce the model order to whatever you want
ReducedModel=modred(ballancedModel,ReduceStatesTo:NumberOfStatesInOldModel);
The initial conditions must of course also be trimmed to the right number of states

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