Data-Driven Stabilization Using Prior Knowledge on Stabilizability and Controllability
The study investigates how prior knowledge about system properties like controllability and stabilizability affects data requirements for finding stabilizing feedback laws. It found that knowing a system is controllable does not relax stabilization conditions, but incorporating stabilizability as prior knowledge leads to necessary and sufficient conditions that are weaker than those without any prior knowledge, especially when state data is rank deficient.