how to improve a model predictive control in order to get a lower cost function for the system?
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jana nassereddine
il 17 Apr 2023
Commentato: jana nassereddine
il 5 Mag 2023
Hello everyone,
I have implemented a model predictive control using a plant model (which has some disturbance in it), then I run the model and I got the cost function(figure2) equal to 8, and the inputs and ouptuts as shown in figure 3, and figure 4 shows the performance of the test which looks good, and the last figure include the parameters of the model, and my first question is how can I improve the model (by lowering the cost function)? could it be by changing the state estimation? or something.
and for the parameters of the simulink, they are as follow: constraints for the input and output, Nc, Np and sampling time.
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Emmanouil Tzorakoleftherakis
il 27 Apr 2023
You basically want to get a more aggressive response if I understand correctly, meaning that your outputs will converge faster to the desired values. First thing to try is increase the cost weights on these particular states.
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