I have used model predictive control strategy in order to optimize a linear discrete SISo model.
For example:
$x(t+1)=-2x(t)+4u(t)$
Where I want to regulate my state $x(t)$ at the desired point (a simple regulating problem).
In every step, I predict $20$ future samples such that MPC optimizes next $20$ time instances (prediction horizon$=20$) and obtains $20$ responses for control variable(control horizon $=20$) then based on RHC technique, I just apply $10$ samples to model.
I know both control horizon and prediction horizon are $20$ samples. but what about applied samples ($10$ samples) what can I name my applied samples?
Best Answer
based on an article (Fig.2):
https://doi.org/10.3390/en11030631
control time steps is a word to define the time between control updates and iterative receding horizon optimization.