Efficient Non-Asymptotic Identification of Linear Switching Systems

This paper presents a novel data-driven approach to simultaneously achieve desirable control and system identification objectives in linear switching systems. The proposed algorithm leverages recent advances in non-asymptotic analysis of linear least-square methods to efficiently identify the unknown system parameters within a finite number of steps.