How to optimize a parameter using Nonlinear model predictive controller
5 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
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
0 Kommentare
Antworten (1)
Emmanouil Tzorakoleftherakis
am 22 Feb. 2023
Bearbeitet: Emmanouil Tzorakoleftherakis
am 23 Feb. 2023
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.
4 Kommentare
Emmanouil Tzorakoleftherakis
am 23 Feb. 2023
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
Siehe auch
Kategorien
Mehr zu Refinement finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!