Dynamic Output-Feedback Controller Synthesis for Dissipativity and $H_2$ Performance from Noisy Input-State Data

In this paper we propose dynamic output-feedback controller synthesis methods for discrete-time linear time-invariant systems.

The synthesis goal is to achieve dissipativity with respect to a given quadratic supply rate or a given $H_2$ performance level.

It is assumed that the model of system dynamics is unknown, expect for the disturbance term.

Instead, we have a recorded trajectory of the control input and the state, which can be corrupted by an unknown but bounded disturbance.

The state data is used only for the purpose of controller synthesis, while the designed controller is output feedback controller, i.e., the full state is not used for control in real time.

The presented synthesis method is formulated in terms of linear matrix inequalities parametrized by a scalar variable, while in noiseless case it reduces to linear matrix inequalities.

Within the considered setting, the synthesis procedure is non-conservative.