Talk:Beginning with CVX
From Wikimization
(Difference between revisions)
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</pre> | </pre> | ||
-------------------------------------------------------------------- | -------------------------------------------------------------------- | ||
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| - | The paper its: Pole assignment of linear uncertain systems in a sector via a lyapunov - tipe approach. D. Arzeiler, J. Bernussou and G. Garcia. IEEE transactions automatic control, vol 38, nº 7, July 1993. | ||
Thanks a lot for all the ideas, they all are greats. | Thanks a lot for all the ideas, they all are greats. | ||
| - | I don't know how to initialice Epsilon1 and Epsilon2 | + | I don't know how to initialice Epsilon1 and Epsilon2. At the article don't put anything. |
| + | |||
| + | I put off the while structure. | ||
Thanks a lot again. | Thanks a lot again. | ||
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Here is the new code: | Here is the new code: | ||
| - | <pre> | + | <pre>%0)Initialization |
| - | %0)Initialization | + | |
clear all; | clear all; | ||
n=2; m=1; | n=2; m=1; | ||
| Line 42: | Line 41: | ||
end | end | ||
| + | %while para==0 | ||
%3)3 | %3)3 | ||
[v_W,D] = eig( full ( W ) ) | [v_W,D] = eig( full ( W ) ) | ||
| Line 119: | Line 119: | ||
end | end | ||
| - | lamda_W = min ( eig ( full ( W ) ) ) | ||
| - | lamda_H = max ( eig ( full ( H ) ) ) | ||
R | R | ||
W=full(W) | W=full(W) | ||
K=R/W | K=R/W | ||
| - | |||
</pre> | </pre> | ||
Revision as of 10:02, 5 February 2009
lamda_W=eig(full(W))
Thanks a lot for all the ideas, they all are greats.
I don't know how to initialice Epsilon1 and Epsilon2. At the article don't put anything.
I put off the while structure.
Thanks a lot again.
Here is the new code:
%0)Initialization
clear all;
n=2; m=1;
A_a=3*eye(2*n,2*n)
B_a=4*eye(2*n,2*m)
%1)1
W=eye(4)
R=(zeros(2,4))
%2)2
H=W*A_a'+A_a*W-B_a*R-R'*B_a'
lamda_W=min(eig(full(W)))
lamda_H=max(eig(H))
Epsilon1=11;
Epsilon2=0.1;
if(lamda_W>=Epsilon1)
if(lamda_H<=-Epsilon2) para=1
else para = 0
end
else para =0
end
%while para==0
%3)3
[v_W,D] = eig( full ( W ) )
[v_H,D] = eig( full ( H ) )
v_W_1 = v_W( : , 1 ) / norm ( v_W ( : , 1 ) ) ;
v_W_2 = v_W( : , 2 ) / norm ( v_W ( : , 2 ) ) ;
v_W_3 = v_W( : , 3 ) / norm ( v_W ( : , 3 ) ) ;
v_W_4 = v_W( : , 4 ) / norm ( v_W ( : , 4 ) ) ;
v_H_1 = v_H( : , 1 ) / norm ( v_H ( : , 1 ) ) ;
v_H_2 = v_H( : , 2 ) / norm ( v_H ( : , 2 ) ) ;
v_H_3 = v_H( : , 3 ) / norm ( v_H ( : , 3 ) ) ;
v_H_4 = v_H( : , 4 ) / norm ( v_H ( : , 4 ) ) ;
%4a)4a
if ( Epsilon1 - lamda_W )>(lamda_H+Epsilon2)
Caso=1 %For know where am I
cvx_begin
variables p1 p2 W(4,4) R(2,4)
minimize (p1+p2)
subject to
W(1,1)<=p1
W(2,2)<=p1
W(1,1)>=Epsilon1
W(2,2)>=Epsilon1
W(3,3)==W(1,1)
W(4,4)==W(2,2)
R(1,1)>=-p2
R(1,1)<=p2
R(2,3)==R(1,1)
R(1,2)>=-p2
R(1,2)<=p2
R(2,4)==R(1,2)
H=W*A_a'+A_a*W-B_a*R-R'*B_a'
v_W'*W*v_W - Epsilon1*eye(2*n) == semidefinite(2*n);
cvx_end
else %4b)4b
Caso = 2
cvx_begin
variables p1 p2 W(4,4) R(2,4)
minimize (p1+p2)
subject to
W(1,1)>=Epsilon1
W(2,2)>=Epsilon1
W(1,1)<=p1
W(2,2)<=p1
W(3,3)==W(1,1)
W(4,4)==W(2,2)
R(1,1)>=-p2
R(1,1)<=p2
R(2,3)==R(1,1)
R(1,2)>=-p2
R(1,2)<=p2
R(2,4)==R(1,2)
H=W*A_a'+A_a*W-B_a*R-R'*B_a'
Epsilon2*eye(2*n) + v_H'*H*v_H == -semidefinite(2*n);
cvx_end
end
R
W=full(W)
K=R/W