Willems’ Fundamental Lemma for Linear Descriptor Systems and Its Use for Data-Driven Output-Feedback MPC

In this letter we investigate data-driven predictive control of discrete-time linear descriptor systems. Specifically, give a tailored variant Willems’ fundamental lemma, which shows that for systems the non-parametric modeling via Hankel matrix requires less data compared to time-invariant without algebraic constraints. Moreover, use description propose framework optimal and For latter, provide sufficient stability condition receding-horizon before illustrate our findings with an example.