Adopting Genetic algorithm for a Simulink model without feedback loop

this is the marx impulse model created in simulink. want to get the rise time - 1.2 us(micro seconds), fall time -50 us, by adjusting the resistance and capacitance values with the help of genetic algorithms. how to do that

Answer 1

[Sam Chak]

Hi @vinusan

I'm unfamiliar with your Simulink model as well as the cost function that is related to Rise Time and Fall Time. However, you can basically call the ga() function using the script below to return the vector k that consists the local optimum resistance R and capacitance C values.

You are advised to study some examples here:

https://www.mathworks.com/help/gads/ga.html

fun = @costfun;
⋮
[k, fval, exitflag, output] = ga(fun, nvars, A, b, Aeq, beq, lb, ub, nonlcon, options)

function J = costfun(k)
    t0 = 0;         % start time
    tf = 20;        % final time
    h  = 1e-2;      % time step size
    opts   = simset('SrcWorkspace', 'current', 'DstWorkspace', 'current');
    simOut = sim('MySimulinkModel', [t0:h:tf], opts);   % Simulink file
    cumJ   = simOut.logsout.get(1).Values.Data;         % cumulative_J
    J      = cumJ(end);                                  
end