Controller Synthesis from Noisy-Input Noisy-Output Data
Lidong Li Andrea Bisoffi Claudio De Persis Nima Monshizadeh
We consider the problem of synthesizing a dynamic output-feedback controller
for a linear system, using solely input-output data corrupted by measurement
noise. To handle input-output data, an auxiliary representation of the original
system is introduced. By exploiting the structure of the auxiliary system, we
design a controller that robustly stabilizes all possible systems consistent
with data. Notably, we also provide a novel solution to extend the results to
generic multi-input multi-output systems. The findings are illustrated by
numerical examples.