Not enough input arguments when doing global optinisation

I am trying to use the global optimisation toolbox to find some parameters which will make a computed curve overlay some experimental data. So I have two pieces of experimental data, t_data and V_data which I want to fit to and I have other sources of experimental data which I use in my function: I_app,SOC_a,SOC_c,OCV_c,OCV_a. I store the parameters I want to find in a colum vector, X. I define the function as follows:

fun = @(X,t_data)terminal_voltage(V_data,I_app,mu_n,t_data,X,SOC_a,SOC_c,OCV_c,OCV_a)';

I define a starting position X_0, and upper and lower bounds UB & LB. The mu_n is just some points I calculate offline. I ran the following code:

rng default % For reproducibility

gs = GlobalSearch;

problem = createOptimProblem('fmincon','x0',X_0,...

'objective',fun,'lb',LB,'ub',UB);

>> x = run(gs,problem);

and I received the following error:

Not enough input arguments.

Error in @(X,t_data)terminal_voltage(V_data,I_app,mu_n,t_data,X,SOC_a,SOC_c,OCV_c,OCV_a)'

Error in fmincon (line 546)

initVals.f = feval(funfcn{3},X,varargin{:});

Error in globalsearchnlp

Error in GlobalSearch/run (line 340)

globalsearchnlp(FUN,X0,A,B,Aeq,Beq,LB,UB,NONLCON,options,localOptions);

Caused by:

Failure in initial objective function evaluation. FMINCON cannot continue.

Failure in initial call to fmincon with user-supplied problem structure.

Any idea what's going on?

Answer 1

[Matthew Hunt]

I've seen what I need to do. The set up of the function is different to lsqcurvefit: I had to define the function as:

fun = @(X,t_data)terminal_voltage(V_data,I_app,mu_n,t_data,X,SOC_a,SOC_c,OCV_c,OCV_a)';

and I had to make my subjective function spit out a scalar rather than a vector so I had to make the function a norm.

It's running now. I have 10 parameters to find, any idea how long it will take?