maximum likelihood estimation with fminsearch

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Hello, I would like to do a maximum likelihood estimation of normal function with the help of fminsearch. It is already working when I dont have any constraints for mu and sigma. I get the estimated mu, sigma and its value of the likelihood function. However, i will fix mu=0 but the resulting mu is never exactly 0 at the end. I dont understand why and in wich way i could do it better.

My code:

first_guess=[0 2];
[Mu_Sigma,Lk] = fminsearch('nlglklySACCzeroMu',first_guess,data);
MuEstimate(2) = Mu_Sigma(1);
SigmaEstimate(2) = Mu_Sigma(2);
L(2)=Lk;

---- next function

function L = nlglklySACCzeroMu(guess)
global data;
guess(1)=0;
if guess(2) < 0
  L = inf;
else
      l=-0.5*log(2*pi)-log(guess(2))-0.5*( data/guess(2) ).^2;
      L = -sum(l);
end