Linear Time-Periodic System Identification with Grouped Atomic Norm Regularization
- Conference Paper
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. Show more
Book title21th IFAC World Congress. Proceedings
Journal / seriesIFAC-PapersOnLine
Pages / Article No.
SubjectSystem identification; regularization; periodic systems
Organisational unit08814 - Smith, Roy (Tit.-Prof.)
178890 - Modeling, Identification and Control of Periodic Systems in Energy Applications (SNF)
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Is supplemented by: https://doi.org/10.3929/ethz-b-000463825
NotesDue to the Coronavirus (COVID-19) the 21st IFAC World Congress 2020 became the 1st Virtual IFAC World Congress (IFAC-V 2020).
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