no code implementations • 7 May 2024 • Jiabao He, Cristian R. Rojas, Håkan Hjalmarsson
There exists many algorithms where these parameters are estimated using least-squares in a first, pre-processing, step, including subspace identification and multi-step least-squares algorithms, such as Weighted Null-Space Fitting.
no code implementations • 7 May 2024 • Jiabao He, Cristian R. Rojas, Håkan Hjalmarsson
Subspace identification methods (SIMs) have proven very powerful for estimating linear state-space models.
no code implementations • 26 Apr 2024 • Jiabao He, Ingvar Ziemann, Cristian R. Rojas, Håkan Hjalmarsson
While subspace identification methods (SIMs) are appealing due to their simple parameterization for MIMO systems and robust numerical realizations, a comprehensive statistical analysis of SIMs remains an open problem, especially in the non-asymptotic regime.
no code implementations • 14 Mar 2022 • Jiabao He, Xuan Zhang, Feng Xu, Junbo Tan, Xueqian Wang
Given the recent surge of interest in data-driven control, this paper proposes a two-step method to study robust data-driven control for a parameter-unknown linear time-invariant (LTI) system that is affected by energy-bounded noises.
no code implementations • 7 Dec 2021 • Jiabao He, Xuan Zhang, Feng Xu, Junbo Tan, Xueqian Wang
For a parameter-unknown linear descriptor system, this paper proposes data-driven methods to testify the system's type and controllability and then to stabilize it.