Fitting 4 data sets to non-linear least squares

Hello there,

Im trying to fit 4 data sets to an analytical model. Im looking for K1, where K1(u,v,r,theta). It gives me a "Exiting due to infeasibility: 1 lower bound exceeds the corresponding upper bound" error I´m pretty sure is because the 4 parameters as lsqcurvefit seems it works only with 2 sets of data, and I have 4. For data, you can use the attached txt file. Thanks in advance JGD0008

This is my code: *************

clear all; close all; clc; format long
E=200000; % MPa
nu=0.3; % poisson
global G k  u v;
G=E/(2*(1+nu)); % shear mod
k=(3-nu)/(1+nu); %kolosov
A = xlsread('img55_DCT.xlsx'); %excel file with experimental data

x=A(:,1); y=A(:,2);
u=A(:,3); 
v=A(:,4);

[m,n]=size(A);
r=zeros(m,1);
theta=zeros(m,1);

for i = 1:1:m %angle rotation according to Irving´s Ref System (X to left, Y down)
    r(i,1)=sqrt(x(i,1)^2+y(i,1)^2);
            if    x(i,1) >= 0 &&  y(i,1)>=0 % I Q
                  theta(i,1)=acos(x(i,1)/r(i,1)); %IQ
            end
            if    x(i,1) < 0 &&  y(i,1)>=0 % II Q
                  theta(i,1)=acos(x(i,1)/r(i,1)); %II Q
            end
            if    x(i,1) < 0 &&  y(i,1)<0 % III Q
                  theta(i,1)=-acos(x(i,1)/r(i,1)); %-I Q
            end  
            if    x(i,1) > 0 &&  y(i,1)<0 % IV Q
                  theta(i,1)=-acos(x(i,1)/r(i,1)); %-II Q
            end  
end

% x0 = [1 25]; % initial guess K1 & K2
x0 = 30; % initial guess K1

% [K1, K2] = lsqcurvefit(@series,x0,r,theta); % two parameters
[K1, resnorm]= lsqcurvefit(@series,x0,r,theta, u, v);
****************
%function

function fseries = series(K1,r,theta)
global G k  u v;
fseries=2*G*sqrt(2*pi./r)*(u./(sin(theta/2)*(k+1+2*(cos(theta/2))^2))-v./(cos(theta/2)*(k-1-2*(sin(theta/2))^2)))-K1(1);
***************

[Alan Weiss]

Please edit your code using the {} Code button so that we can read it.

Alan Weiss

MATLAB mathematical toolbox documentation

[jgd0008]

thanks