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P = AUGW(G,W1,W2,W3)
P = AUGW(G,W1,W2,W3) computes a state-space model of an augmented LTI plant P(s) with weighting functions W1(s), W2(s), and W3(s) penalizing the error signal, control signal and output signal respectively (see block diagram) so that the closed-loop transfer function matrix is the weighted mixed sensitivity

where S, R and T are given by

The LTI systems S and T are called the sensitivity and complementary sensitivity, respectively.
Plant Augmentation

For dimensional compatibility, each of the three weights W1, W2 and W3 must be either empty, a scalar (SISO) or have respective input dimensions Ny, Nu, and Ny where G is Ny-by-Nu. If one of the weights is not needed, you may simply assign an empty matrix [ ]; e.g., P = AUGW(G,W1,[],W3) is P(s) as in the Algorithms section below, but without the second row (without the row containing W2).
The augmented plant P(s) produced by is

Partitioning is embedded via P=mktito(P,NY,NU), which sets the InputGroup and OutputGroup properties of P as follows
[r,c]=size(P);
P.InputGroup = struct('U1',1:c-NU,'U2',c-NU+1:c);
P.OutputGroup = struct('Y1',1:r-NY,'Y2',r-NY+1:r);
s=zpk('s'); G=(s-1)/(s+1);
W1=0.1*(s+100)/(100*s+1); W2=0.1; W3=[];
P=augw(G,W1,W2,W3);
[K,CL,GAM]=hinfsyn(P); [K2,CL2,GAM2]=h2syn(P);
L=G*K; S=inv(1+L); T=1-S; sigma(S,'k',GAM/W1,'k-.',T,'r',GAM*G/W2,'r-.')
legend('S = 1/(1+L)','GAM/W1', 'T=L/(1+L)','GAM*G/W2',2)

The transfer functions G, W1, W2 and W3 must
be proper,
i.e., bounded as
or, in the discrete-time
case, as
. Additionally, W1, W2 and W3 should
be stable. The plant G should be stabilizable and
detectable; else, P will not be stabilizable by
any K.
h2syn | hinfsyn | mixsyn | mktito

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