Why LMI toolbox/ Yalmip get a semi-positive definite matrix as the answer?

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!!!

Answers (1)

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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Asked:

on 19 Aug 2013

Commented:

on 6 Jul 2018

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