Error: objective function (feval) is not zero or at optimum.

I am trying to use mle estimation to estimate parameters of customized pdf. I am using two methods: mle function and fmincon. The function I am trying to estimate has the following sotchastic distribution: f(x)=(1-c)/(sqrt(2*pi*)*op)*exp(-power(x-up,2)*0.5*op^-2) +(c)/(sqrt(2*pi*)*oz)*exp(-power(x-up-uz,2)*0.5*op^-2)

where c is a bionomial random variable.

the objective function using mle and fmincon does not progress to 0 (feval at the optimum is 4.7 e3). First optimality order is zero. This is the code that I have used for fmincon :

z=x(1,:);

options = optimoptions('fmincon','Display','iter-detailed','Algorithm','sqp','MaxIter',3e4,'MaxFunctionEvaluations',3e8,....
    'StepTolerance',1e-10,'TolFun',1e-3,'OptimalityTolerance',1e-5,'ConstraintTolerance',1e-3 ,'FiniteDifferenceType','central')
problem.options = options;
% rng('default');
problem.solver = 'fmincon';%'TolX',10^-4,'TolFun',10^-4,
problem.objective = @(y)norm_likelhood_fun(y,z);%norm_likelhood_multi_fun(y,z);%
problem.x0 = rand(5,1);
problem.nonlcon = @(y) cdf_norm(y,z);
problem.A = []; 
problem.b = [];
problem.Aeq = [];
problem.beq = [];
problem.lb = 0*ones(5,1);
problem.ub = 1*ones(5,1);%[0.99 0.99 0.99 0.99 0.99];
gs = GlobalSearch;
ms=MultiStart;
%problem.ub = [1,1,1,1,1];
%for j=1:1
problem.x0= [0.1 1e-2 0 0.05 1e-2];

%problem.x0 = [0;0.1;0;0.2;0.01];
 [y,feval ,exitflag,output,lam]=fmincon(problem)

yy=[u1;o1;u2;o2;ep]





function l1=norm_likelhood_fun(y,z,cens,freq)

                oz=sqrt(y(2).^2+y(4).^2);
                x1=((1-y(5))/(sqrt(2*pi)*y(2)))*exp(-0.5*power(z(~cens)-y(1),2)/y(2)^2);
                x2=(y(5)/(sqrt(2*pi)*oz))*exp(-0.5*power(z(~cens)-y(1)-y(3),2)/oz^2);
                l1=-sum(log(x1+x2));
end 





function [c,ceq]=cdf_norm(y,z)

 oz=sqrt(y(2).^2+y(4).^2);
 x1=((1-y(5))/(2))*(1+erf((z-y(1))/(y(2)*sqrt(2))));
 x2=(y(5)/2)*(1+erf((z-y(1)-y(3))/(oz*sqrt(2))));
 c=-1+x1+x2;
 ceq=[];

end 

I followed the recommendation on the below links:

https://www.mathworks.com/help/optim/ug/when-the-solver-might-have-succeeded.html

https://www.mathworks.com/help/optim/ug/when-the-solver-fails.html

However, the ouput that i got is this:

Iter  Func-count            Fval   Feasibility   Step Length       Norm of   First-order  
                                                                       step    optimality
   30         369    5.495456e+03     0.000e+00     1.000e+00     4.031e-03     2.805e+00  
   31         380    5.495456e+03     0.000e+00     1.000e+00     9.287e-03     3.505e+00  
   32         391    5.495455e+03     0.000e+00     1.000e+00     1.933e-02     3.550e+00  
   33         402    5.495455e+03     0.000e+00     1.000e+00     2.312e-02     3.031e+00  
   34         413    5.495455e+03     0.000e+00     1.000e+00     3.105e-03     1.810e-01  
   35         424    5.495455e+03     0.000e+00     1.000e+00     3.168e-03     5.573e-01  
   36         435    5.495455e+03     0.000e+00     1.000e+00     2.338e-03     7.707e-01  
   37         446    5.495455e+03     0.000e+00     1.000e+00     5.335e-03     9.047e-01  
   38         457    5.495455e+03     0.000e+00     1.000e+00     4.379e-03     6.183e-01  
   39         468    5.495455e+03     0.000e+00     1.000e+00     3.938e-03     1.542e-01  
   40         479    5.495455e+03     0.000e+00     1.000e+00     4.085e-03     1.323e-01  
   41         490    5.495455e+03     0.000e+00     1.000e+00     3.578e-03     9.856e-02  
   42         501    5.495455e+03     0.000e+00     1.000e+00     2.611e-03     4.071e-02  
   43         512    5.495455e+03     0.000e+00     1.000e+00     2.386e-03     5.575e-02  
   44         523    5.495455e+03     0.000e+00     1.000e+00     2.003e-03     1.303e-02  
   45         535    5.495455e+03     0.000e+00     7.000e-01     2.057e-03     5.140e-02  
   46         546    5.495455e+03     0.000e+00     1.000e+00     6.619e-05     1.113e-02  
   47         557    5.495455e+03     0.000e+00     1.000e+00     8.599e-04     5.128e-03  
   48         569    5.495455e+03     0.000e+00     7.000e-01     2.112e-03     2.619e-02  
   49         580    5.495455e+03     0.000e+00     1.000e+00     8.720e-04     1.873e-03  
   50         591    5.495455e+03     0.000e+00     1.000e+00     3.328e-04     8.088e-05  
   51         607    5.495455e+03     0.000e+00     1.681e-01     1.968e-05     4.356e-05  
   52         618    5.495455e+03     0.000e+00     1.000e+00     1.233e-05     5.707e-06  

Optimization completed: The relative first-order optimality measure, 5.707383e-06,
is less than options.OptimalityTolerance = 1.000000e-05, and the relative maximum constraint
violation, 0.000000e+00, is less than options.ConstraintTolerance = 1.000000e-03.


y =

    0.3264    0.4192         0    0.0033    0.0304


feval =

   5.4955e+03


exitflag =

     1


output = 

  struct with fields:

         iterations: 52
          funcCount: 618
          algorithm: 'sqp'
            message: '↵Local minimum found that satisfies the constraints.↵↵Optimization completed because the objective function is non-decreasing in ↵feasible directions, to within the value of the optimality tolerance,↵and constraints are satisfied to within the value of the constraint tolerance.↵↵<stopping criteria details>↵↵Optimization completed: The relative first-order optimality measure, 5.707383e-06,↵is less than options.OptimalityTolerance = 1.000000e-05, and the relative maximum constraint↵violation, 0.000000e+00, is less than options.ConstraintTolerance = 1.000000e-03.↵↵'
    constrviolation: 0
           stepsize: 1.2330e-05
       lssteplength: 1
      firstorderopt: 5.7074e-06