MATLAB: Lsqcurvefit nonlinear model: experimental data with model prediction

lsqcurvefitnonlinear curve least squares

Hello, I am trying to fit a curve with non linear model (as shown in the caption). I used lsqcurvefit. The fitted curve is bad. How can I get a better fit and another question how can i fit two data simultaneously (same xdata but different ydata, for each ydata same function but i just want to change the value "80"). Thank you in advance. (the data is in attachment) 
figure;
A=importdata('ouss.xlsx');
xdata = ...
 (A(:,1));
ydata = ...
 (A(:,2));
%%


% Create a simple exponential decay model.
fun = @(x,xdata)(x(1)*exp(-(x(2)*(80-x(4)))/(x(3)+80-x(4))))...
        ./(1+(xdata*(x(1)*exp(-(x(2)*(80-x(4)))/(x(3)+80-x(4))))./x(6)).^(1-x(5)));
%%
% Fit the model using the starting point 
x0 = [2e+05,12.3,10.12,335,0.37,12.3];
% x0 = [1,1,1,1,1,1];
options = optimoptions('lsqcurvefit','Algorithm','levenberg-marquardt','Display','iter','TolX', 1e-20, 'TolFun', 1e-20, 'MaxFunEvals', 40000, 'MaxIter', 4000000);
lb = [1 1 1 1 0 1];
ub = [1e17 100 100 1000 1 1e9];
[x] =  lsqcurvefit(fun,x0,xdata,ydata,lb,ub,options)
%%
% Plot the data and the fitted curve.
times = linspace(xdata(1),xdata(end));
loglog(xdata,ydata,'ko',times,fun(x,times),'b-')
legend('Data','Fitted exponential')
title('Data and Fitted Curve')

Best Answer

how can i fit two data simultaneously (same xdata but different ydata, for each ydata same function but i just want to change the value "80").
Just concatenate the data together and write a bigger model function with more variables that describes both.
https://www.mathworks.com/matlabcentral/answers/431697-make-curve-fitting-faster
For a small number of fits, however, it's usually not worthwhile.
How can I get a better fit
I find that fitting the log of the data gives better results,
[x] =  lsqcurvefit(@(p,xd)log(fun(p,xd)),x0,xdata,log(ydata),lb,ub,options);
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