Why LMI toolbox/ Yalmip get a semi-positive definite matrix as the answer?
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I recently was do something about optimizing control. In my simulations, I already set the constraints with P>0, but the LMI toolbox/Yalmip returned me a answer as following:
P=[21.0930 0.0101 -21.0926 -0.0100;
0.0101 0.1467 -0.0100 -0.1467;
-21.0926 -0.0100 21.0922 0.0100;
-0.0100 -0.1467 0.0100 0.1467]
while eig(P)=[ 0.0000 0.0000 0.2934 42.1852]. As you can see, there are two zero eigenvalues of this P, it's not positive definite!
Could anybody explain this to me??? Many thanks!!!
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Answers (1)
Johan Löfberg
on 14 Nov 2013
Edited: Johan Löfberg
on 14 Nov 2013
Strict inequalities are not really supported
BTW, you get much faster response on
https://groups.google.com/forum/?fromgroups#!forum/yalmip
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