2023/04/06 by Jiayun Li, Li, Jiayun, Yilin Mo +1
Engineering · #Control Systems and Identification #FOS: Mathematics #Fault Detection and Control Systems #Optimization and Control (math.OC) #Structural Health Monitoring Techniques
paper · pdf · doi:10.48550/arxiv.2304.03024
openalex publication_date 2023/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes an identification algorithm for Single Input Single Output (SISO) Linear Time-Invariant (LTI) systems. In the noise-free setting, where the first T Markov parameters can be precisely estimated, all Markov parameters can be inferred by the linear combination of the known T Markov parameters, of which the coefficients are obtained by solving the uniform polynomial approximation problem, and the upper bound of the asymptotic identification bias is provided. For the finite-time identification scenario, we cast the system identification problem with noisy Markov parameters into a regularized uniform approximation problem. Numerical results demonstrate that the proposed algorithm outperforms the conventional Ho-Kalman Algorithm for the finite-time identification scenario while the asymptotic bias remains negligible.