From System Level Synthesis to Robust Closed-loop Data-enabled Predictive Control

원문 초록

The Willems' fundamental lemma and the system level synthesis characterize trajectories generated by a linear system. While the former method is valid for deterministic LTI systems, the latter one is further effective for stochastic linear time varying systems. In this paper, these two methods offers equivalent characterization of stochastic LTI systems. Inspired by this observation, a robust closed-loop data-enabled predictive control scheme is proposed for stochastic LTI systems. A causal feedback structure is further derived, leading to an computational cost similar to standard robust MPC with full state measurements. The proposed method is validated by a second order system a single-zone building control problem.