3 ms·
The trick is that, even though the augmented state is uncontrollable, you still use it in the predictions, so the MPC algorithm can still compensate for it. Tak
by pidtuner 5y ago
The trick is that, even though the augmented state is uncontrollable, you still use it in the predictions, so the MPC algorithm can still compensate for it. Take a look at the before-last graph in the paper, see how that technique improves predictions after learning the real-time disturbances.
- gugagore 5y agoThat's not what I was concerned about. The subspace that's uncontrollable is the disturbance components of the state, which I don't care to control anyway.
- pidtuner 5y agoNot to control, but to compensate. This is what the I action in the PID does, compensate for un-modeled disturbances