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Not enough input arguments when doing global optinisation

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Matthew Hunt
Matthew Hunt on 21 Feb 2019
Answered: Matthew Hunt on 21 Feb 2019
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,...
>> 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)
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?

Answers (1)

Matthew Hunt
Matthew Hunt on 21 Feb 2019
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?

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