# Talk:Beginning with CVX

### From Wikimization

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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 | + | The code still not working. I think I’m making thinks wrong (sure). I have a dude. |

- | + | The new code could be: | |

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<pre> | <pre> | ||

%0)Initialization | %0)Initialization | ||

clear all; | clear all; | ||

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+ | %cvx_setup | ||

n=2; m=1; | n=2; m=1; | ||

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lamda_W=min(eig(full(W))) | lamda_W=min(eig(full(W))) | ||

lamda_H=max(eig(H)) | lamda_H=max(eig(H)) | ||

- | + | Epsilon1=1e-6; | |

- | Epsilon1= | + | Epsilon2=1e-6; |

- | Epsilon2= | + | %3)3 |

- | + | [v_W,D] = eig( full ( W ) ) | |

- | + | [v_H,D] = eig( full ( H ) ) | |

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- | 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 ) ) ; | ||

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- | 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 ) ) ; | ||

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- | %4a)4a | ||

- | if ( Epsilon1 - lamda_W )>(lamda_H+Epsilon2) | ||

- | Caso=1 %For know where am I | ||

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cvx_begin | cvx_begin | ||

variables p1 p2 W(4,4) R(2,4) | variables p1 p2 W(4,4) R(2,4) | ||

+ | if ( Epsilon1 - lamda_W )>(lamda_H+Epsilon2) CK=v_W'*W*v_W - Epsilon1*eye(2*n) ; | ||

+ | else CK=-Epsilon2*eye(2*n) - v_H'*H*v_H ; | ||

+ | end | ||

+ | |||

+ | minimize (p1+p2) | ||

- | + | subject to | |

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- | + | 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) | |

- | + | CK == semidefinite(2*n); | |

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cvx_end | cvx_end | ||

- | end | ||

lamda_W = min ( eig ( full ( W ) ) ) | lamda_W = min ( eig ( full ( W ) ) ) |

## Current revision

lamda_W=eig(full(W))

Thanks a lot for all the ideas, they all are greats.

The code still not working. I think I’m making thinks wrong (sure). I have a dude.

The new code could be:

%0)Initialization clear all; %cvx_setup 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=1e-6; Epsilon2=1e-6; %3)3 [v_W,D] = eig( full ( W ) ) [v_H,D] = eig( full ( H ) ) cvx_begin variables p1 p2 W(4,4) R(2,4) if ( Epsilon1 - lamda_W )>(lamda_H+Epsilon2) CK=v_W'*W*v_W - Epsilon1*eye(2*n) ; else CK=-Epsilon2*eye(2*n) - v_H'*H*v_H ; end 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) CK == semidefinite(2*n); cvx_end lamda_W = min ( eig ( full ( W ) ) ) lamda_H = max ( eig ( full ( H ) ) ) R W=full(W) K=R/W