MATLAB: Error messages during using Genetic algorithm and lsqnonlin optimization functions

curve fittingerrorgenetic algorithmMATLABnonlinearoptimization

Currently,I am running optimization script file by using the outputs from the genetic algorithm function in the least square nonlinear function lsqnonlin() (as initial values for lsqnonlin()).When I run the script ,the following errors appear.So,what's the problem ?
Optimization terminated: maximum number of generations exceeded.
Error using snls (line 48)
Objective function is returning undefined values at initial
point. lsqnonlin cannot continue.
Error in lsqncommon (line 150)
    [xC,FVAL,LAMBDA,JACOB,EXITFLAG,OUTPUT,msgData]=...
Error in lsqnonlin (line 237)
[xCurrent,Resnorm,FVAL,EXITFLAG,OUTPUT,LAMBDA,JACOB] = ...
Error in frf (line 27)
[c,resnorm,residual,exitflag1,output1]=lsqnonlin(ff,c0);
Here is the code:
clc
clear all
% Create an anonymous function that describes the expected relationship
% between X and Y
f=@(c,x) exp((c(1).*(x(:,1).^c(2)))+(x(:,3)*c(4))+(x(:,2)*c(3)))+c(5).*(((x(:,2))./(x(:,3))-0.5).^2)+c(6).*(x(:,2))+c(7);
% data set 
% Specify x variables from data file,Re,Theta and Beta columns.
x=xlsread('all data for fitting friction');
% Specify y variable from data file ,(f)column.
y=x(:,4);
% objective function 
ff=@(c)(f(c,x)-y)./y;
% maximum of objective function
ffmax=@(c)norm(ff(c));
% Identifying population size and number of parameters for genetic
% algorithm
PopSz = 400;
Parms = 7;
% Modifying the options of genetic algotithm optimization function
opts = gaoptimset('PopulationSize',PopSz, 'InitialPopulation',randi(1E+4,PopSz,Parms)*1E-4, 'Generations',2e3,'StallGenLimit',inf, 'PlotFcn',@gaplotbestf, 'PlotInterval',1);
% Genetic algorithm application
[theta,fval,exitflag,output] = ga(ffmax, Parms, [],[],[],[],-Inf(Parms,1),Inf(Parms,1),[],[],opts);
% Specify a vector of starting conditions for the solvers(Least squre
% nnonlinear fit)
c0=[theta(1) ;theta(2);theta(3);theta(4);theta(5);theta(6);theta(7)];
% Perform a nonlinear regression
[c,resnorm,residual,exitflag1,output1]=lsqnonlin(ff,c0);
y1=f(c,x);
diff_f=y-y1;
Abs_diff_f=abs(diff_f);
perc_error=(Abs_diff_f./y);
x_line45=0:max(y);y_line45=0:max(y);
[max_error,I_max]=max(perc_error);
[min_error,I_min]=min(perc_error);
x_line_high=0:max(y); y_line_high=(max_error+1)*(0:max(y));
x_line_low=0:max(y); y_line_low=(1-max_error)*(0:max(y));
figure
plot(x_line45,y_line45,'k')
hold on
scatter(y,y1)
hold on
plot(x_line_high,y_line_high,'r')
hold on
plot(x_line_low,y_line_low,'r')
header=['fact','ffit'];
N=[y,y1];
disp(header)
disp(N)
disp('max. error=')
disp(max_error)

Best Answer

You have quite a few NaNs in your y data
>> nnz(isnan(y))
ans =
     7
>> nnz(isnan(ff(theta)))
ans =
     7
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