How can I stop errors in Simulink and Simscape?

Hello eveyone,

I am trying to build an basketball shooting arm model with simscape. I got motion capture data and I am trying to create the model according to motion capture motion. To do this I have to optimize 42 parameters and I am using Simulated Annealing Algorithm to optimize them. Everything is ready but I got a problem.

Line 118 runs the simularion and at the end of the simulation, Line 120 gives me the simularion results as a matrix.

My code is like that:

  %% .... blah blah blah .....
  
118- sim('basketball_shooting_simulation.slx')
119
120-out_table= [ans.out_shoulder.time,ans.out_shoulder.signals.values,ans.out_elbow.signals.values,ans.out_wrist.signals.values];
121-assignin('base','ans',ans)
122-t_s=(0:0.004:0.312);
123-angle_results = out_table(ismembertol(out_table(:,1),t_s),:);
124-assignin('base','angle_results',angle_results)

%% after this step bring the results to comparison function .....

When I start the optimization program, it runs several times and it stops immediately because of the simscape errors like:

An error occurred while running the simulation and the simulation was terminated

Caused by:

• Derivative of state 'basketball_shooting_simulation.Basketball_Shooting_Arm_Model.shoulder_joint.Rz.w' in block 'basketball_shooting_simulation/Basketball Shooting Arm Model/shoulder joint' at time 0.220275 is not finite. The simulation will be stopped. There may be a singularity in the solution. If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances)

As we can understand here I don't want to use this run's parameters and optimization must be continue but it is not. After this error everything stops immediately.

How can I get the lastes results of simulation without errors and continue the optimization?

I would be appeciate I you can help me.

[Yifeng Tang]

Maybe use a try ... catch ... syntax for the simulation call? When it fails and falls to a "catch", assign some garbage output that the optimizer will hate.