How to solve optimization problem with squared error sum in Simulink

Hi, I have a Simulink model with 4 PIDs and a non-linear plant. I wrote a script running a sdo.SimulationTest and logging the output data and the input data of the model. Then I calculated the squared error sum J. Is it possible to use an optimizer minimizing this squared error sum and using the Parameters of the PID as variables. There is no functional connection between these two. Below is my code. Thank you

 startSimulator;
sim_obj=sdo.SimulationTest('Hummingbird_Simulation_PositionControl_original')
Param=param.Continuous([2;1.5;2;2;1.5;2;5;1;2.8]);
Param.Minimum=[0;0;0;0;0;0;0;0;0];
Param.Maximum=[10;10;10;10;10;10;10;10;10];
sim_obj.Parameters=Param;
sim_obj.LoggingInfo.LoggingMode='LogAllAsSpecifiedInModel';
sim_out=sim(sim_obj);
Y_x=sim_out.LoggedData.get('logsout').getElement('X').Values;
Y_y=sim_out.LoggedData.get('logsout').getElement('Y').Values;
Y_z=sim_out.LoggedData.get('logsout').getElement('Z').Values;
W_x=sim_out.LoggedData.get('logsout').getElement('X_cmd').Values;
W_y=sim_out.LoggedData.get('logsout').getElement('Y_cmd').Values;
W_z=sim_out.LoggedData.get('logsout').getElement('Z_cmd').Values;
W=[W_x.get('Data') W_y.get('Data') W_z.get('Data')];
Y=[Y_x.get('Data') Y_y.get('Data') Y_z.get('Data')];
length=length(W);
time=W_x.time;
E=[(W(1:length,1)-Y(1:length,1)).^2 (W(1:length,2)-Y(1:length,2)).^2 (W(1:length,3)-Y(1:length,3)).^2];
J=sum(sum(E));
  end

[Birdman]

Can you also share your model as well?

[FloRida]

Here it is. Hope this helps. Thx