Linear Time-Periodic System Identification with Grouped Atomic Norm Regularization
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Author / Producer
Date
2020-11
Publication Type
Conference Paper
ETH Bibliography
yes
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Abstract
This paper proposes a new methodology in linear time-periodic (LTP) system identification. In contrast to previous methods that totally separate dynamics at different tag times for identification, the method focuses on imposing appropriate structural constraints on the linear time-invariant (LTI) reformulation of LTP systems. This method adopts a periodically-switched truncated infinite impulse response model for LTP systems, where the structural constraints are interpreted as the requirement to place the poles of the non-truncated models at the same locations for all sub-models. This constraint is imposed by combining the atomic norm regularization framework for LTI systems with the group lasso technique in regression. As a result, the estimated system is both uniform and low-order, which is hard to achieve with other existing estimators. Monte Carlo simulation shows that the grouped atomic norm method does not only show better results compared to other regularized methods, but also outperforms the subspace identification method under high noise levels in terms of model fitting.
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Publication status
published
External links
Book title
21st IFAC World Congress
Journal / series
Volume
53 (2)
Pages / Article No.
1237 - 1242
Publisher
Elsevier
Event
21st IFAC World Congress (IFAC-V 2020)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
System identification; regularization; periodic systems
Organisational unit
08814 - Smith, Roy (Tit.-Prof.) (ehemalig) / Smith, Roy (Tit.-Prof.) (former)
Notes
Due to the Coronavirus (COVID-19) the 21st IFAC World Congress 2020 became the 1st Virtual IFAC World Congress (IFAC-V 2020).
Funding
178890 - Modeling, Identification and Control of Periodic Systems in Energy Applications (SNF)
Related publications and datasets
Is supplemented by: https://doi.org/10.3929/ethz-b-000463825