Iterative Data-driven Control Design for Unknown Linear Systems: A System Theoretic Analysis

This article analyzes the fundamental mechanisms and properties of indirect and direct data-driven policy iteration methods for solving the linear quadratic regulator (LQR) problem when the system dynamics are unknown. The analysis provides insights into the role of system identification in establishing convergence, sample complexity, and robustness.