How to optimize a parameter using Nonlinear model predictive controller
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Hello everyone,
I am using Nonlinear model predictive controller and I wonder if I can optimize a parameter.
Let's take an example Plan Optimal Trajectory Using Nonlinear MPC on this website (https://www.mathworks.com/help/mpc/ref/nlmpc.nlmpcmove.html). In FlyingRobotStateFcn.m there are 2 given parameters alpha and beta = 0.2. Is there a way to make these paremeters also variables and calculate optimal values of alpha and beta ?
Thank you for your answers
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Emmanouil Tzorakoleftherakis
2023-2-22
编辑:Emmanouil Tzorakoleftherakis
2023-2-23
Looks like you are referring to parameters defined inside the prediction model/state function of the MPC controller. You can make these variables parameters/arguments to the state function by following the guidelines on this page.
To use MPC for static optimization, one idea is to use the parameter as an MV and set a MVRate constraint to zero. That would basically make this MV constant. That way you could have both dynamically changing MVs and a constant one. If you try it, please let me know if it works.
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Emmanouil Tzorakoleftherakis
2023-2-23
I see. So basically you have mixed dynamic and static decision variables. I haven't tried it myself, but one idea is to still use the parameter as an MV and set a MVRate constraint to zero. That would basically make this MV constant. That way you could have both dynamically changing MVs and a constant one. If you try it, please let me know if it works.
I also updated my answer accordingly
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