How to do parameter estimation of a ODE based model through Global Optimization Toolbox?

I have a ODE based model and a set of experimental data for my project. There are seven parameters (Constant) inside the model need to do parameter estimation through GA solver. My fitness function/Objective function will be sum of quadratic difference between simulated and experimental result.

I had saw someone proposed that " Implement your model, write a cost function, and use Optimization Toolbox to minimize this cost function by fitting parameters to have model output match the data." in the previous question.

Could anyone elaborate how to work with the method above or any tutorial on it? Thanks in advance!

Answer 1

[Shashank Prasanna]

More details on how you would go about fitting an ODE using optimization:

http://www.mathworks.com/help/optim/ug/optimizing-a-simulation-or-ordinary-differential-equation.html